Datasets:

ftopal
/

huggingface-datasets-raw

Dataset card Data Studio Files Files and versions Community

Split (1)

train · 109k rows

sha stringlengths 40 40	text stringlengths 0 13.4M	id stringlengths 2 117	tags sequence	created_at stringlengths 25 25	metadata stringlengths 2 31.7M	last_modified stringlengths 25 25
5d3139b44137e785ac86c73f1eb0d96f99eabc08	# Dataset Card for Nexdata/German_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/65?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data set contains 327 German native speakers' speech data. The recording contents include economics, entertainment, news, oral, figure, letter, etc. Each sentence contains 10.3 words on average. Each sentence is repeated 1.4 times on average. All texts are manually transcribed to ensure the high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/65?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages German ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/German_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T06:57:37+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:35:35+00:00
445bb0917556a70ad236551fe3b97436b6534eb1	# Dataset Card for Nexdata/European_Portuguese_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/953?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It is speech data of 2,000 Portuguese natives with authentic accents. The recorded text is designed by professional language experts and is rich in content, covering multiple categories such as general purpose, interactive, vehicle-mounted and household commands. The recording environment is quiet and without echo. The texts are manually transcribed with a high accuracy rate. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/953?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Portuguese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/European_Portuguese_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T06:58:58+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:33:15+00:00
b20644e28084db6d1ae97febf2b834510f486835	# Dataset Card for Nexdata/Italian_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/67?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Italian speech data (reading) is collected from 325 Italian native speakers and is recorded in quiet environment. The recording is rich in content, covering multiple categories such as econimics, entertainment, news, and oral. Each sentence contains 9.2 words in average. Each sentence is repeated 2.7 times on average. All texts are manual transcribed with high accuray. For more details, please refer to the link: https://www.nexdata.ai/datasets/67?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Italian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Italian_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T07:00:44+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T02:31:13+00:00
2dcf218f28bacd4f98e62369efd3b0a23d1dd3f3	# Dataset Card for Nexdata/Thai_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/69?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Thai speech data (reading) is collected from 498 Thailand native speakers and is recorded in quiet environment. The recording is rich in content, covering multiple categories such as econimics, entertainment, news, figure, and oral. Around 400 sentences for each speaker. The valid data volumn is 292 hours. All texts are manual transcribed with high accuray. For more details, please refer to the link: https://www.nexdata.ai/datasets/69?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Thai ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Thai_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T07:03:53+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T03:21:51+00:00
a826b2d97de822902048c37b1ff19c6a3afcb159	# Dataset Card for Nexdata/Indonesian_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/71?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Indonesia speech data (reading) is collected from 496 Indonesian native speakers and is recorded in quiet environment. The recording is rich in content, covering multiple categories such as econimics, entertainment, news, figure, letter, and oral. Around 400 sentences for each speaker. The valid data volumn is 360 hours. All texts are manual transcribed with high accuray. For more details, please refer to the link: https://www.nexdata.ai/datasets/71?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Indonesian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Indonesian_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T07:05:34+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:52:19+00:00
2ca0a3875fdc7f503d1b39d67a6a5d194cd7a2f3	# Dataset Card for Nexdata/Malay_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/73?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 156 Speakers - Mobile Telephony Malay Speech Data_Reading is recorded by native Malay speakers in the quiet environment. The recording is rich in content, covering multiple categories such as economy, entertainment, news, oral language, numbers, and letters. Around 450 sentences for each speaker. The effective time is 134 hours. All texts are manually transcribed to ensure high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/73?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Malay ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Malay_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T07:08:28+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:52:44+00:00
db412a0f35c8316a47cf7b92dc2f7bc235e14b4c	# Dataset Card for Nexdata/American_Children_Speech_Data_by_Microphone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/75?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It is recorded by 219 American children native speakers. The recording texts are mainly storybook, children's song, spoken expressions, etc. 350 sentences for each speaker. Each sentence contain 4.5 words in average. Each sentence is repeated 2.1 times in average. The recording device is hi-fi Blueyeti microphone. The texts are manually transcribed. For more details, please refer to the link: https://www.nexdata.ai/datasets/75?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages American English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/American_Children_Speech_Data_by_Microphone	[ "region:us" ]	2022-06-21T07:10:59+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:55:25+00:00
431c9e8c892142adbc924606ceb99960b010769a	# Dataset Card for Nexdata/Chinese_Young_Children_Speech_Data_by_Mobile_Phone_and_Microphone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: hhttps://www.nexdata.ai/datasets/76?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data were recorded by 797 Chinese children aged 3 to 5, of whom 39% were children aged 5. The recording content conforms to the characteristics of children, mainly storybooks, children's songs, spoken language. Around 120 sentences for each speaker. It is simultaneously recorded by hi-fi microphone and cellphone. The vaild data are 41.8 hours. Texts are manually transcribed with high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/76?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Mandarin Chinese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Young_Children_Speech_Data_by_Mobile_Phone_and_Microphone	[ "region:us" ]	2022-06-21T07:12:06+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:43:46+00:00
2cbeb4ce29dfdba9d8be53faec991d07e26cf071	# Dataset Card for Nexdata/British_English_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/80?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data set contains 346 British English speakers' speech data, all of whom are English locals. Around 392 sentences of each speaker. The valid data is 199 hours. Recording environment is quiet. Recording contents contain various categories like economics, news, entertainment, commonly used spoken language, letter, figure, etc. For more details, please refer to the link: https://www.nexdata.ai/datasets/80?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages British English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/British_English_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-21T07:14:51+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:43:22+00:00
b524d03cf8dfffffb3bb8c01876e1c75db9ed88c	# Dataset Card for Nexdata/Spanish_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/951?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data volumn is 435 hours and is recorded by 989 Spanish native speakers. The recording text is designed by linguistic experts, which covers general interactive, in-car and home category. The texts are manually proofread with high accuracy. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/951?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Spanish_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:24:36+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-31T01:30:51+00:00
67822f9347f26473632e92b782999caf41a0bd84	# Dataset Card for Nexdata/Brazilian_Portuguese_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/954?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data volumn is 1044 hours and is recorded by 2038 Brazilian native speakers. The recording text is designed by linguistic experts, which covers general interactive, in-car and home category. The texts are manually proofread with high accuracy. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/954?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Brazilian Portuguese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Brazilian_Portuguese_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:26:02+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:47:05+00:00
d514392e817ed921ddefc4d8e93a69236dc6144c	# Dataset Card for Nexdata/French_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/952?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data volumn is 769 hours and is recorded by 1623 French native speakers. The recording text is designed by linguistic experts, which covers general interactive, in-car and home category. The texts are manually proofread with high accuracy. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/952?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages French ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/French_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:27:28+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:47:30+00:00
13587f1d88a2e7bfd134aaec7931a39e6f240a21	# Dataset Card for Nexdata/Number_Speech_Data_in_Mandarin_and_Dialects_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/250?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Digital dialect Mandarin audio data captured by mobile phone, with the duration of 66 hours; 592 people participated in the recording, with balanced gender distribution; the languages include Sichuan dialect, Cantonese, and Mandarin; content covers daily life scenes; matching with mainstream Android, Apple system mobile phones; this data set can be used for automatic speech recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/250?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Mandarin, Chinese Dialects ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Number_Speech_Data_in_Mandarin_and_Dialects_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:28:47+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:48:04+00:00
fbd42148b2e3e5375590fbd560ca0aa547007f94	# Dataset Card for Nexdata/Chinese_Wake-up_Words_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/177?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Chinese wake-up words audio data captured by mobile phone, collected from 200 people, 180 sentences per person, a total length of 24.5 hours; recording staff come from seven dialect regions with balanced gender distribution; collection environment was diversified; recorded text includes wake-up words and colloquial sentences. For more details, please refer to the link: https://www.nexdata.ai/datasets/177?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Mandarin Chinsese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Wake-up_Words_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:30:24+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:44:15+00:00
e56625c159f30812db9b9ed55229af3af6824d4d	# Dataset Card for Nexdata/Russian_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/976?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1960 Russian native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, in-vehicle and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/976?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Russian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Russian_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:31:48+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:48:36+00:00
3224e326520bf11956ae45e93c0f38beced5a1d6	# Dataset Card for Nexdata/Chinese_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1002?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1,279 Chinese speakers from major dialect regions participated in the recording, it is in line with the specific accent of Chinese English speakers. The recorded script cover many categories such as spoken English, speech, and human-computer interaction, rich in content, extensive in fields, and balanced in phonemes. It can be used to improve the recognition effect of the automatic speech recognition system on Chinese people speaking English. For more details, please refer to the link: https://www.nexdata.ai/datasets/1002?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:34:20+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:44:38+00:00
efa7c24d6ebb364dd7b2df64a3f8c18864fa1ce7	# Dataset Card for Nexdata/Vietnamese_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1006?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1751 Vietnamese native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and covers a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/1006?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Vietnamese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Vietnamese_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:36:28+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:48:44+00:00
94d89d94e3b7ed226b24106292f12a0a4fb452d7	# Dataset Card for Nexdata/Latin_American_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1021?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 281 Latinos recorded in a relatively quiet environment in authentic English. The recorded script is designed by linguists and covers a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/1021?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Latin American English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Latin_American_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:37:57+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:49:40+00:00
62ddb18d01fa7a85ad7e4e752c0633a07e30e592	# Dataset Card for Nexdata/Canadian_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1047?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 466 native Canadian speakers involved, balanced for gender. The recording corpus is rich in content, and it covers a wide domain such as generic command and control category, human-machine interaction category; smart home category; in-car category. The transcription corpus has been manually proofread to ensure high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/1047?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Canadian English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Canadian_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:39:25+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:50:07+00:00
c78b4f4e292d0517f2df781f41bf4beb9da12adc	# Dataset Card for Nexdata/Japanese_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1048?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 400 native Japanese speakers involved, balanced for gender. The recording corpus is rich in content, and it covers a wide domain such as generic command and control category, human-machine interaction category; smart home category; in-car category. The transcription corpus has been manually proofread to ensure high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/1048?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Japanese English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Japanese_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:40:43+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:49:18+00:00
025e0726c12dfeadfb82b982f8a2b448c767eb3c	# Dataset Card for Nexdata/Mixed_Speech_with_Korean_and_English_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1114?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is recorded by Korean native speakers . The recorded text is a mixture of Korean and English sentences, covering general scenes and human-computer interaction scenes. It is rich in content and accurate in transcription. It can be used for improving the recognition effect of the speech recognition system on Korean-English mixed reading speech. For more details, please refer to the link: https://www.nexdata.ai/datasets/1114?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Korean, English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mixed_Speech_with_Korean_and_English_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:43:55+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:49:13+00:00
09f0f979da25146c65c56c0837206df8902b8eef	# Dataset Card for Nexdata/Filipino_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1124?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1000 Hours Filipino English audio data captured by mobile phones, recorded by Filipino native speakers. The recorded text is designed by linguistic experts, covering generic, interactive, on-board, home and other categories. The text has been proofread manually with high accuracy; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/1124?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Filipino English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Filipino_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-21T07:46:06+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:46:36+00:00
e31c1e5c1868a5b9a58673217bc0c9d8f823d82e	# Dataset Card for Nexdata/Japanese_Synthesis_Corpus-Female ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1165?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 10.4 Hours - Japanese Synthesis Corpus-Female. It is recorded by Japanese native speaker, with authentic accent. The phoneme coverage is balanced. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/1165?source=Huggingface ### Supported Tasks and Leaderboards tts: The dataset can be used to train a model for Text to Speech (TTS). ### Languages Japanese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Japanese_Synthesis_Corpus-Female	[ "region:us" ]	2022-06-21T07:47:59+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:42:55+00:00
48a38cd86da2f78ac31fbd5b637b7851d57c6aab	# Dataset Card for Nexdata/Interspeech2020_Accented_English_Speech_Recognition_Competition_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1169?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Interspeech2,020 Accented English Speech Recognition Competition Data. The text has been proofread manually with high accuracy; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/1169?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Accented English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Interspeech2020_Accented_English_Speech_Recognition_Competition_Data	[ "region:us" ]	2022-06-21T07:49:40+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:49:40+00:00
c9ccf96a8fea3c88f5573b8a11228e0122a3c7cc	# SentEval Customer Reviews This dataset is a port of the official [SentEval `CR` dataset](https://nlp.stanford.edu/~sidaw/home/projects:nbsvm) from [this paper](https://dl.acm.org/doi/10.1145/1014052.1014073). The test split was created from the by randomly sampling 20% of the original data and the train split is the remaining 80%. there are no official train/test splits of CR. There is no validation split. This was used in the STraTA paper.	SetFit/SentEval-CR	[ "region:us" ]	2022-06-21T07:52:19+00:00	{}	2022-06-21T08:14:00+00:00
dc97bcce7a228120beb6fc597484b6aea9222c3a	# CT-EBM-SP (Clinical Trials for Evidence-based Medicine in Spanish) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: http://www.lllf.uam.es/ESP/nlpmedterm_en.html - Repository: http://www.lllf.uam.es/ESP/nlpdata/wp2/CT-EBM-SP.zip - Paper: Campillos-Llanos, L., Valverde-Mateos, A., Capllonch-Carrión, A., & Moreno-Sandoval, A. (2021). A clinical trials corpus annotated with UMLS entities to enhance the access to evidence-based medicine. BMC medical informatics and decision making, 21(1), 1-19 - Point of Contact: leonardo.campillos AT gmail.com ### Dataset Summary The [Clinical Trials for Evidence-Based-Medicine in Spanish corpus](http://www.lllf.uam.es/ESP/nlpdata/wp2/) is a collection of 1200 texts about clinical trials studies and clinical trials announcements: - 500 abstracts from journals published under a Creative Commons license, e.g. available in PubMed or the Scientific Electronic Library Online (SciELO) - 700 clinical trials announcements published in the European Clinical Trials Register and Repositorio Español de Estudios Clínicos If you use the CT-EBM-SP resource, please, cite as follows: ``` @article{campillosetal-midm2021, title = {A clinical trials corpus annotated with UMLS© entities to enhance the access to Evidence-Based Medicine}, author = {Campillos-Llanos, Leonardo and Valverde-Mateos, Ana and Capllonch-Carri{\'o}n, Adri{\'a}n and Moreno-Sandoval, Antonio}, journal = {BMC Medical Informatics and Decision Making}, volume={21}, number={1}, pages={1--19}, year={2021}, publisher={BioMed Central} } ``` ### Supported Tasks Medical Named Entity Recognition ### Languages Spanish ## Dataset Structure ### Data Instances - 292 173 tokens - 46 699 entities of the following [Unified Medical Language System (UMLS)](https://www.nlm.nih.gov/research/umls/index.html) semantic groups: - ANAT (anatomy and body parts): 6728 entities - CHEM (chemical and pharmacological substances): 9224 entities - DISO (pathologic conditions): 13 067 entities - PROC (therapeutic and diagnostic procedures, and laboratory analyses): 17 680 entities ### Data Splits - Train: 175 203 tokens, 28 101 entities - Development: 58 670 tokens, 9629 entities - Test: 58 300 tokens, 8969 entities ## Dataset Creation ### Source Data - Abstracts from journals published under a Creative Commons license, available in [PubMed](https://pubmed.ncbi.nlm.nih.gov/) or the [Scientific Electronic Library Online (SciELO)](https://scielo.org/es/) - Clinical trials announcements published in the [European Clinical Trials Register](https://www.clinicaltrialsregister.eu) and [Repositorio Español de Estudios Clínicos](https://reec.aemps.es) ### Annotations #### Who are the annotators? - Leonardo Campillos-Llanos, Computational Linguist, Consejo Superior de Investigaciones Científicas - Adrián Capllonch-Carrión, Medical Doctor, Centro de Salud Retiro, Hospital Universitario Gregorio Marañón - Ana Valverde-Mateos, Medical Lexicographer, Spanish Royal Academy of Medicine ## Considerations for Using the Data Disclosure: This dataset is under development and needs to be improved. It should not be used for medical decision making without human assistance and supervision. This resource is intended for a generalist purpose, and may have bias and/or any other undesirable distortions. The owner or creator of the models will in no event be liable for any results arising from the use made by third parties of this dataset. Descargo de responsabilidad: Este conjunto de datos se encuentra en desarrollo y no debe ser empleada para la toma de decisiones médicas La finalidad de este modelo es generalista, y puede tener sesgos y/u otro tipo de distorsiones indeseables. El propietario o creador de los modelos de ningún modo será responsable de los resultados derivados del uso que las terceras partes hagan de estos datos.	lcampillos/ctebmsp	[ "task_categories:token-classification", "task_ids:named-entity-recognition", "multilinguality:monolingual", "language:es", "license:cc-by-4.0", "region:us" ]	2022-06-21T08:35:11+00:00	{"language": ["es"], "license": "cc-by-4.0", "multilinguality": ["monolingual"], "task_categories": ["token-classification"], "task_ids": ["named-entity-recognition"], "pretty_name": ["CT-EBM-SP"]}	2022-07-23T21:48:56+00:00
9e6b82e3134265d63fad9308eb996dbe21b2653c	# Dataset Card for CLIP-Kinetics70 ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Dataset Preprocessing](#dataset-preprocessing) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Source Data](#source-data) - [Simple Experiments](#dataset-creation) - [Zero-shot Evaluation](#zero-shot) - [Linear-probe Evaluation](#zero-shot) ## Dataset Description ### Dataset Summary CLIP-Kinetics700 is a compressed version of the Kinetics700 dataset using OpenAI's CLIP model. The original dataset is ~700 GB making it difficult to use and hold in memory on one machine. By downsampling each video to 1 FPS and encoding the frames using CLIP we we're able to compress the dataset to ~8 GB making it very memory-friendly and easy to use. ### Dataset Preprocessing [clip-video-encode](https://github.com/iejMac/clip-video-encode) is a tool you can use to easily and efficiently compute CLIP embeddings from video frames. We used it to generate the embeddings for this dataset. ## Dataset Structure ### Data Format We formatted this as a [WebDataset](https://github.com/webdataset/webdataset) for better data-loading performance when training the models. Each split contains a list of tar files each with 10000 data samples. This format can be read and used easily using the EmbeddingWebDatasetReader from [clip-video-encode](https://github.com/iejMac/clip-video-encode). ``` CLIP-Kinetics700 ├── splits.csv ├── ds_00000.tar \| ├── vid_00000.npy \| ├── vid_00000.txt \| ├── vid_00000.json \| ├── vid_00001.npy \| ├── vid_00001.txt \| ├── vid_00001.json \| └── ... \| ├── vid_10000.npy \| ├── vid_10000.txt \| ├── vid_10000.json ├── ds_00001.tar \| ├── vid_10001.npy \| ├── vid_10001.txt \| ├── vid_10001.json │ ... ... ``` ### Data Fields * vid.npy: the numpy array with the per-frame embeddings. Shape -> (n_frames, 512) * vid.cap: the "caption" of the video. In this case it is the Kinetics700 label. * vid.json: additional metadata - YouTube video ID, start time, end time. ### Data Splits * Train - 536489 samples \| 54 tar's * Validation - 33966 samples \| 4 tar's * Test - 64532 samples \| 7 tar's ## Dataset Creation ### Source Data Data was sourced from DeepMind's [Kinetics700](https://www.deepmind.com/open-source/kinetics) dataset and downloaded using [this](https://github.com/cvdfoundation/kinetics-dataset) convenient repository. ## Simple Experiments Using [this repository](https://github.com/LAION-AI/temporal-embedding-aggregation) we evaluate CLIP-Kinetics700 with the following simple methods: ### [Zero-shot Evaluation](https://github.com/LAION-AI/temporal-embedding-aggregation/blob/master/src/evaluation/zero_shot.py) \| \| Accuracy \| \| ---------------- \| -------- \| \| Top-1 \| 0.31 \| \| Top-5 \| 0.56 \| \| mean(Top1, Top5) \| 0.44 \| ### [Linear-probe Evaluation](https://github.com/LAION-AI/temporal-embedding-aggregation/blob/master/src/evaluation/linear_probe.py) \| \| Accuracy \| \| ---------------- \| -------- \| \| Top-1 \| 0.41 \| \| Top-5 \| 0.65 \| \| mean(Top1, Top5) \| 0.53 \|	iejMac/CLIP-Kinetics700	[ "task_categories:feature-extraction", "task_categories:zero-shot-classification", "annotations_creators:found", "language_creators:found", "multilinguality:monolingual", "size_categories:100K<n<1M", "language:en", "license:mit", "region:us" ]	2022-06-21T09:49:29+00:00	{"annotations_creators": ["found"], "language_creators": ["found"], "language": ["en"], "license": ["mit"], "multilinguality": ["monolingual"], "size_categories": ["100K<n<1M"], "task_categories": ["feature-extraction", "zero-shot-classification"], "pretty_name": "CLIP-Kinetics700"}	2022-07-11T16:21:32+00:00
495a499ae501478e2e934c453964d9bf5cd103eb	# GitHub Jupyter Dataset ## Dataset Description The dataset was extracted from Jupyter Notebooks on BigQuery. ## Licenses Each example has the license of its associated repository. There are in total 15 licenses: ```python [ 'mit', 'apache-2.0', 'gpl-3.0', 'gpl-2.0', 'bsd-3-clause', 'agpl-3.0', 'lgpl-3.0', 'lgpl-2.1', 'bsd-2-clause', 'cc0-1.0', 'epl-1.0', 'mpl-2.0', 'unlicense', 'isc', 'artistic-2.0' ] ```	codeparrot/github-jupyter	[ "task_categories:text-generation", "task_ids:language-modeling", "language_creators:crowdsourced", "language_creators:expert-generated", "multilinguality:muonolingual", "size_categories:unknown", "language:code", "license:other", "region:us" ]	2022-06-21T10:45:11+00:00	{"annotations_creators": [], "language_creators": ["crowdsourced", "expert-generated"], "language": ["code"], "license": ["other"], "multilinguality": ["muonolingual"], "size_categories": ["unknown"], "source_datasets": [], "task_categories": ["text-generation"], "task_ids": ["language-modeling"]}	2022-10-25T08:30:04+00:00
1bacaa7115661e44f6d60aeaab8c641333334463	# Laion-Face [LAION-Face](https://github.com/FacePerceiver/LAION-Face) is the human face subset of [LAION-400M](https://laion.ai/laion-400-open-dataset/), it consists of 50 million image-text pairs. Face detection is conducted to find images with faces. Apart from the 50 million full-set(LAION-Face 50M), there is a 20 million sub-set(LAION-Face 20M) for fast evaluation. LAION-Face is first used as the training set of [FaRL](https://github.com/FacePerceiver/FaRL), which provides powerful pre-training transformer backbones for face analysis tasks. For more details, please check the offical repo at https://github.com/FacePerceiver/LAION-Face . ## Download and convert metadata ```bash wget -l1 -r --no-parent https://the-eye.eu/public/AI/cah/laion400m-met-release/laion400m-meta/ mv the-eye.eu/public/AI/cah/laion400m-met-release/laion400m-meta/ . wget https://huggingface.co/datasets/FacePerceiver/laion-face/resolve/main/laion_face_ids.pth wget https://raw.githubusercontent.com/FacePerceiver/LAION-Face/master/convert_parquet.py python convert_parquet.py ./laion_face_ids.pth ./laion400m-meta ./laion_face_meta ``` ## Download the images with img2dataset When metadata is ready, you can start download the images. ```bash wget https://raw.githubusercontent.com/FacePerceiver/LAION-Face/master/download.sh bash download.sh ./laion_face_meta ./laion_face_data ``` Please be patient, this command might run over days, and cost about 2T disk space, and it will download 50 million image-text pairs as 32 parts. - To use the LAION-Face 50M, you should use all the 32 parts. - To use the LAION-Face 20M, you should use these parts. ``` 0,2,5,8,13,15,17,18,21,22,24,25,28 ``` checkout `download.sh` and [img2dataset](https://github.com/rom1504/img2dataset) for more details and parameter setting.	FacePerceiver/laion-face	[ "region:us" ]	2022-06-21T12:28:35+00:00	{}	2022-11-18T04:04:56+00:00
8753c2788d36c01fc6f05d03fe3f7268d63f9122	# SummEval The annotations include summaries generated by 16 models from 100 source news articles (1600 examples in total). Each of the summaries was annotated by 5 indepedent crowdsource workers and 3 independent experts (8 annotations in total). Summaries were evaluated across 4 dimensions: coherence, consistency, fluency, relevance. Each source news article comes with the original reference from the CNN/DailyMail dataset and 10 additional crowdsources reference summaries. For this dataset, we averaged the 3 expert annotations to get the human scores. source: https://github.com/Yale-LILY/SummEval	mteb/summeval	[ "language:en", "region:us" ]	2022-06-21T12:37:10+00:00	{"language": ["en"]}	2022-09-27T18:14:10+00:00
8fa2b4ee823448830f62d48cd0cd21357bede874	# Dataset Card for `tldr_news` ## Table of Contents - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-instances) - [Data Splits](#data-instances) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) ## Dataset Description - Homepage: https://tldr.tech/newsletter ### Dataset Summary The `tldr_news` dataset was constructed by collecting a daily tech newsletter (available [here](https://tldr.tech/newsletter)). Then, for every piece of news, the `headline` and its corresponding ` content` were extracted. Also, the newsletter contain different sections. We add this extra information to every piece of news. Such a dataset can be used to train a model to generate a headline from a input piece of text. ### Supported Tasks and Leaderboards There is no official supported tasks nor leaderboard for this dataset. However, it could be used for the following tasks: - summarization - headline generation ### Languages en ## Dataset Structure ### Data Instances A data point comprises a "headline" and its corresponding "content". An example is as follows: ``` { "headline": "Cana Unveils Molecular Beverage Printer, a ‘Netflix for Drinks’ That Can Make Nearly Any Type of Beverage ", "content": "Cana has unveiled a drink machine that can synthesize almost any drink. The machine uses a cartridge that contains flavor compounds that can be combined to create the flavor of nearly any type of drink. It is about the size of a toaster and could potentially save people from throwing hundreds of containers away every month by allowing people to create whatever drinks they want at home. Around $30 million was spent building Cana’s proprietary hardware platform and chemistry system. Cana plans to start full production of the device and will release pricing by the end of February.", "category": "Science and Futuristic Technology" } ``` ### Data Fields - `headline (str)`: the piece of news' headline - `content (str)`: the piece of news - `category (str)`: newsletter section ### Data Splits - `all`: all existing daily newsletters available [here](https://tldr.tech/newsletter). ## Dataset Creation ### Curation Rationale This dataset was obtained by scrapping the collecting all the existing newsletter available [here](https://tldr.tech/newsletter). Every single newsletter was then processed to extract all the different pieces of news. Then for every collected piece of news the headline and the news content were extracted. ### Source Data #### Initial Data Collection and Normalization The dataset was has been collected from https://tldr.tech/newsletter. In order to clean up the samples and to construct a dataset better suited for headline generation we have applied a couple of normalization steps: 1. The headlines initially contain an estimated read time in parentheses; we stripped this information from the headline. 2. Some news are sponsored and thus do not belong to any newsletter section. We create an additional category "Sponsor" for such samples. #### Who are the source language producers? The people (or person) behind the https://tldr.tech/ newsletter. ### Annotations #### Annotation process Disclaimers: The dataset was generated from a daily newsletter. The author had no intention for those newsletters to be used as such. #### Who are the annotators? The newsletters were written by the people behind TLDR tech. ### Personal and Sensitive Information [Needs More Information] ## Considerations for Using the Data ### Social Impact of Dataset [Needs More Information] ### Discussion of Biases This dataset only contains tech news. A model trained on such a dataset might not be able to generalize to other domain. ### Other Known Limitations [Needs More Information] ## Additional Information ### Dataset Curators The dataset was obtained by collecting newsletters from this website: https://tldr.tech/newsletter ### Contributions Thanks to [@JulesBelveze](https://github.com/JulesBelveze) for adding this dataset.	JulesBelveze/tldr_news	[ "task_categories:summarization", "task_categories:text2text-generation", "task_categories:text-generation", "task_ids:news-articles-headline-generation", "task_ids:text-simplification", "task_ids:language-modeling", "annotations_creators:other", "language_creators:other", "multilinguality:monolingual", "size_categories:1K<n<10K", "source_datasets:original", "language:en", "region:us" ]	2022-06-21T13:35:34+00:00	{"annotations_creators": ["other"], "language_creators": ["other"], "language": ["en"], "multilinguality": ["monolingual"], "size_categories": ["1K<n<10K"], "source_datasets": ["original"], "task_categories": ["summarization", "text2text-generation", "text-generation"], "task_ids": ["news-articles-headline-generation", "text-simplification", "language-modeling"], "pretty_name": "tldr_news"}	2022-08-05T11:17:50+00:00
468c80b863113e2e27d3777cbc3786d18f9e5308	## COLD: Complex Offensive Language Dataset If you use this dataset, please cite the following paper (BibTex below): Alexis Palmer, Christine Carr, Melissa Robinson, and Jordan Sanders. 2020 (to appear). COLD: Annotation scheme and evaluation data set for complex offensive language in English. Journal of Linguistics and Computational Linguistics. ## Overview of data The COLD data set is intended for researchers to diagnose and assess their automatic hate speech detection systems. The corpus highlights 4 different types of complex offensive language: slurs, reclaimed slurs, adjective nominalization, distancing, and also non-offensive texts. The corpus contains a set of tweets collected from 3 different data sets: Davidson et al (2017), Waseem and Hovy (2016), and Robinson (2017). The data is annotated by 6 annotators, with each instance being annotated by at least 3 different annotators. COLD-2016 is the data set used for the analyses and experimental results described in the JLCL paper. This version of the data set contains 2016 instances, selected using filters aiming to capture the complex offensive language types listed above. ## Format and annotations The data are made available here as .tsv files. The format consists of eight columns: four informational and four annotation-related. ### Informational columns: 1. ID - information about the original data set and the textual instance's ID from the data set it was extracted from. The ID includes a letter indicating which data set it originates from, followed by a hyphen and the corresponding ID of the instance in the original data set. For example: D-63 means that the instance is from the Davidson et al. (2017) data set, originally with the ID number 63. 2. Dataset - a letter indicating from which dataset this instance originates. 3. Text - the text of the instance. ### Majority Vote Columns: For each instance, annotators were asked to answer Yes or No to each of four questions. Theses columns are the majority vote from three annotators (See the paper for much more detailed discussion, as well as distributions, etc.) 1. Off Is this text offensive? 2. Slur Is there a slur in the text? 3. Nom Is there an adjectival nominalization in the text? 4. Dist Is there (linguistic) distancing in the text? ### Individual Annotator Columns: For each instance, annotators were asked to answer Yes or No to each of four questions. Theses columns are the individual response from each annotators (See the paper for much more detailed discussion, as well as distributions, etc.) 1. Off1/2/3 Is this text offensive? 2. Slur1/2/3 Is there a slur in the text? 3. Nom1/2/3 Is there an adjectival nominalization in the text? 4. Dist1/2/3 Is there (linguistic) distancing in the text? ### Category 1. Cat This column is deduced based on the majority votes for OFF/SLUR/NOM/DIST. (See the paper for detailed explination the categories, as well as distributions, etc.) ## Contact If you have any questions please contact [email protected], [email protected], or [email protected]. ## BibTex ``` @article{cold:2020, title = {COLD: Annotation scheme and evaluation data set for complex offensive language in English}, author = {Palmer, Alexis and Carr, Christine and Robinson, Melissa and Sanders, Jordan}, journal = {Journal of Linguistics and Computational Linguistics, Special Issue}, year = {2020}, volume={to appear}, number={to appear}, pages = {tbd} } ``` ## References Davidson, T., Wamsley, D., Macy, M., & Weber, I. (2017). Automated hate speech detection and the problem of offensive language. In Eleventh international conference on web and social media. <a href="https://aaai.org/ocs/index.php/ICWSM/ICWSM17/paper/view/15665">[the paper]</a>, <a href="https://github.com/t-davidson/hate-speech-and-offensive-language">[the repository]</a> Robinson, M. (2018). A man needs a female like a fish needs a lobotomy: The role of adjectival nominalization in pejorative meaning. Master's thesis, Department of Linguistics, University of North Texas. <a href="https://digital.library.unt.edu/ark:/67531/metadc1157617/m2/1/high_res_d/ROBINSON-THESIS-2018.pdf">[the thesis]</a> Waseem, Z., & Hovy, D. (2016). Hateful Symbols or Hateful People? Predictive Features for Hate Speech Detection on Twitter. In Proceedings of the NAACL Student Research Workshop. San Diego, California. <a href="https://www.aclweb.org/anthology/N16-2013/">[the paper]</a>	COLD-team/COLD	[ "license:cc-by-sa-4.0", "region:us" ]	2022-06-21T14:53:15+00:00	{"license": "cc-by-sa-4.0"}	2022-06-21T15:38:44+00:00
c14a8424c86c93120a4c9fdce9f5e732cfb9cf2d	From https://zenodo.org/record/6627159#.YrH0dJFBxhE Hyperbard is a dataset of diverse relational data representations derived from Shakespeare's plays. Our representations range from simple graphs capturing character co-occurrence in single scenes to hypergraphs encoding complex communication settings and character contributions as hyperedges with edge-specific node weights. By making multiple intuitive representations readily available for experimentation, we facilitate rigorous representation robustness checks in graph learning, graph mining, and network analysis, highlighting the advantages and drawbacks of specific representations. The code used to create Hyperbard is maintained on GitHub.	osanseviero/hyperbard	[ "region:us" ]	2022-06-21T16:15:50+00:00	{}	2022-06-21T16:17:56+00:00
3d98ae2a9dccba541d3228caab27e20adea5db8b	# GEM Submission Submission name: This is a test name	lewtun/benchmarks-gem-submission	[ "benchmark:gem", "evaluation", "benchmark", "region:us" ]	2022-06-21T19:16:43+00:00	{"benchmark": "gem", "type": "prediction", "submission_name": "This is a test name", "tags": ["evaluation", "benchmark"]}	2022-06-21T19:17:21+00:00
38e208221aaac6fca4e3dcae77ab8c967df2deba	# Dataset Card for Electrical half hourly raw and cleaned datasets for Great Britain from 2008-11-05 ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://zenodo.org/record/6606485 - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary <p><strong>A journal paper published in Energy Strategy Reviews details the method to create the data.</strong></p> <p><strong>https://www.sciencedirect.com/science/article/pii/S2211467X21001280</strong></p> <p> </p> <p>2021-09-09: Version 6.0.0 was created. Now includes data for the North Sea Link (NSL) interconnector from Great Britain to Norway (https://www.northsealink.com). The previous version (5.0.4) should not be used - as there was an error with interconnector data having a static value over the summer 2021.</p> <p> </p> <p>2021-05-05: Version 5.0.0 was created. Datetimes now in ISO 8601 format (with capital letter 'T' between the date and time) rather than previously with a space (to RFC 3339 format) and with an offset to identify both UTC and localtime. MW values now all saved as integers rather than floats. Elexon data as always from www.elexonportal.co.uk/fuelhh, National Grid data from https://data.nationalgrideso.com/demand/historic-demand-data   Raw data now added again for comparison of pre and post cleaning - to allow for training of additional cleaning methods. If using Microsoft Excel, the T between the date and time can be removed using the =SUBSTITUTE() command - and substitute "T" for a space " "</p> <p>_____________________________________________________________________________________________________</p> <p>2021-03-02: Version 4.0.0 was created. Due to a new interconnecter (IFA2 - https://en.wikipedia.org/wiki/IFA-2) being commissioned in Q1 2021, there is an additional column with data from National Grid - this is called 'POWER_NGEM_IFA2_FLOW_MW' in the espeni dataset. In addition, National Grid has dropped the column name 'FRENCH_FLOW' that used to provide the value for the column 'POWER_NGEM_FRENCH_FLOW_MW' in previous espeni versions. However, this has been changed to 'IFA_FLOW' in National Grid's original data, which is now called 'POWER_NGEM_IFA_FLOW_MW' in the espeni dataset. Lastly, the IO14 columns have all been dropped by National Grid - and potentially unlikely to appear again in future.</p> <p>2020-12-02: Version 3.0.0 was created. There was a problem with earlier versions local time format - where the +01:00 value was not carried through into the data properly. Now addressed - therefore - local time now has the format e.g. 2020-03-31 20:00:00+01:00 when in British Summer Time.</p> <p>2020-10-03: Version 2.0.0 was created as it looks like National Grid has had a significant change to the methodology underpinning the embedded wind calculations. The wind profile seems similar to previous values, but with an increasing value in comparison to the value published in earlier the greater the embedded value is. The 'new' values are from https://data.nationalgrideso.com/demand/daily-demand-update from 2013.</p> <p>Previously: raw and cleaned datasets for Great Britain's publicly available electrical data from Elexon (www.elexonportal.co.uk) and National Grid (https://demandforecast.nationalgrid.com/efs_demand_forecast/faces/DataExplorer). Updated versions with more recent data will be uploaded with a differing version number and doi</p> <p>All data is released in accordance with Elexon's disclaimer and reservation of rights.</p> <p>https://www.elexon.co.uk/using-this-website/disclaimer-and-reservation-of-rights/</p> <p>This disclaimer is also felt to cover the data from National Grid, and the parsed data from the Energy Informatics Group at the University of Birmingham.</p> ### Supported Tasks and Leaderboards [More Information Needed] ### Languages The class labels in the dataset are in English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators This dataset was shared by Grant Wilson, Noah Godfrey ### Licensing Information The license for this dataset is https://creativecommons.org/licenses/by-nc/4.0/legalcode ### Citation Information ```bibtex @dataset{grant_wilson_2022_6606485, author = {Grant Wilson and Noah Godfrey}, title = {{Electrical half hourly raw and cleaned datasets for Great Britain from 2008-11-05}}, month = jun, year = 2022, note = {{Grant funding as part of Research Councils (UK) EP/L024756/1 - UK Energy Research Centre research programme Phase 3 Grant funding as part of Research Councils (UK) EP/V012053/1 - The Active Building Centre Research Programme (ABC RP)}}, publisher = {Zenodo}, version = {6.0.9}, doi = {10.5281/zenodo.6606485}, url = {https://doi.org/10.5281/zenodo.6606485} } ``` ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.	nateraw/espeni-2	[ "license:unknown", "region:us" ]	2022-06-21T20:29:31+00:00	{"license": ["unknown"], "zenodo_id": "6606485"}	2022-10-25T09:32:39+00:00
b78f79ebaf2de145a50b3e42746841ed2dd4948e	# Dataset Card for Airbnb Stock Price ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://kaggle.com/datasets/evangower/airbnb-stock-price - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This contains the historical stock price of Airbnb (ticker symbol ABNB) an American company that operates an online marketplace for lodging, primarily homestays for vacation rentals, and tourism activities. Based in San Francisco, California, the platform is accessible via website and mobile app. ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators This dataset was shared by [@evangower](https://kaggle.com/evangower) ### Licensing Information The license for this dataset is cc0-1.0 ### Citation Information ```bibtex [More Information Needed] ``` ### Contributions [More Information Needed]	nateraw/airbnb-stock-price-2	[ "license:cc0-1.0", "region:us" ]	2022-06-21T20:45:36+00:00	{"license": ["cc0-1.0"], "kaggle_id": "evangower/airbnb-stock-price"}	2022-10-25T09:32:42+00:00
a0e2eba82ce143fc4ea8be7aee92e51658f5f046	# Dataset Card for Hyperbard (Dataset) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://zenodo.org/record/6627159 - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary <p>First release of <a href="https://hyperbard.net">Hyperbard</a>.</p> <p>Hyperbard is a dataset of diverse relational data representations derived from Shakespeare's plays. Our representations range from simple graphs capturing character co-occurrence in single scenes to hypergraphs encoding complex communication settings and character contributions as hyperedges with edge-specific node weights. By making multiple intuitive representations readily available for experimentation, we facilitate rigorous representation robustness checks in graph learning, graph mining, and network analysis, highlighting the advantages and drawbacks of specific representations. </p> <p>The code used to create Hyperbard is maintained on <a href="https://github.com/hyperbard/hyperbard">GitHub</a>. </p> ### Supported Tasks and Leaderboards [More Information Needed] ### Languages The class labels in the dataset are in English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators This dataset was shared by Corinna Coupette, Jilles Vreeken, Bastian Rieck ### Licensing Information The license for this dataset is http://creativecommons.org/licenses/by-nc/2.0/ ### Citation Information ```bibtex @dataset{corinna_coupette_2022_6627159, author = {Corinna Coupette and Jilles Vreeken and Bastian Rieck}, title = {Hyperbard (Dataset)}, month = jun, year = 2022, publisher = {Zenodo}, version = {0.0.1}, doi = {10.5281/zenodo.6627159}, url = {https://doi.org/10.5281/zenodo.6627159} } ``` ### Contributions [More Information Needed]	nateraw/hyperbard	[ "license:unknown", "region:us" ]	2022-06-21T22:43:55+00:00	{"license": ["unknown"], "zenodo_id": "6627159"}	2022-10-25T09:32:44+00:00
f7ccc8b77d0322219397180f9c74273637b5393d	# Dataset Card for Lung Cancer ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://kaggle.com/datasets/nancyalaswad90/lung-cancer - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The effectiveness of cancer prediction system helps the people to know their cancer risk with low cost and it also helps the people to take the appropriate decision based on their cancer risk status. The data is collected from the website online lung cancer prediction system . ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators This dataset was shared by [@nancyalaswad90](https://kaggle.com/nancyalaswad90) ### Licensing Information The license for this dataset is cc-by-nc-sa-4.0 ### Citation Information ```bibtex [More Information Needed] ``` ### Contributions [More Information Needed]	nateraw/lung-cancer	[ "license:cc-by-nc-sa-4.0", "region:us" ]	2022-06-21T22:57:00+00:00	{"license": ["cc-by-nc-sa-4.0"], "kaggle_id": "nancyalaswad90/lung-cancer"}	2022-10-25T09:32:46+00:00
6cef6d00028697782bfffebbe4766a081064d389	# Dataset Card for Monkeypox Dataset (Daily Updated) ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://kaggle.com/datasets/deepcontractor/monkeypox-dataset-daily-updated - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary ![](https://forthebadge.com/images/badges/made-with-python.svg) ## Context - Monkeypox is an infectious disease caused by the monkeypox virus that can occur in certain animals, including humans. Symptoms begin with fever, headache, muscle pains, swollen lymph nodes, and feeling tired. - An ongoing outbreak of monkeypox was confirmed on 6 May 2022, beginning with a British resident who, after traveling to Nigeria (where the disease is endemic), presented symptoms consistent with monkeypox on 29 April 2022. The resident returned to the United Kingdom on 4 May, creating the country's index case of the outbreak. ## Content ``` File 1 : Monkey_Pox_Cases_Worldwide Description : This dataset contains a tally of confirmed and suspected cases in all the countries. File 2 : Worldwide_Case_Detection_Timeline Description : This dataset contains the timeline for confirmed cases w.r.t. date time, it also contains some other details on every case that is being reported.\ File 3 : Daily_Country_Wise_Conformed_Cases Description : This dataset contains the daily number of confirmed cases for all the countries where the virus has entered. Thank you @sudalairajkumar for the suggestion. ``` ## Acknowledgements [Globaldothealth Website](https://globalhealth.org/) [Globaldothealth Github](https://github.com/globaldothealth) ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators This dataset was shared by [@deepcontractor](https://kaggle.com/deepcontractor) ### Licensing Information The license for this dataset is cc0-1.0 ### Citation Information ```bibtex [More Information Needed] ``` ### Contributions [More Information Needed]	nateraw/monkeypox	[ "license:cc0-1.0", "region:us" ]	2022-06-21T23:15:30+00:00	{"license": ["cc0-1.0"], "kaggle_id": "deepcontractor/monkeypox-dataset-daily-updated"}	2022-07-08T05:39:52+00:00
ba2d46f92eca0a41b0438638ff7417881c11f401	--- license: afl-3.0 ---?_Trust wallet helpline number ?{+1}-(818)7518351} The most trusted & secure Supp0rt helpline.	trustwallet/support	[ "region:us" ]	2022-06-22T01:11:11+00:00	{}	2022-06-22T01:12:25+00:00
a395c793a51a088175813b4d7628432d9a9e5a8a	# Dataset Card for Demo3 ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This is a demo dataset. It consists in two files `data/train.csv` and `data/test.csv` You can load it with ```python from datasets import load_dataset demo3 = load_dataset("Sampson2022/demo3") ``` ### Supported Tasks and Leaderboards [More Information Needed] ### Languages [More Information Needed] ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information [More Information Needed] ### Citation Information [More Information Needed] ### Contributions Thanks to [@github-username](https://github.com/<github-username>) for adding this dataset.	Sampson2022/demo3	[ "region:us" ]	2022-06-22T01:57:58+00:00	{"type": "demo3"}	2022-06-22T02:20:18+00:00
6ad3bf600fcdf3bdf41e02edaf594ec651073c16	# Vietnamese Text-To-Speech dataset (VBSF001-v1.0) The audio is crawled from audiobooks on YouTube. The audio is NOT for commercial use. The text is labeled by [VinBrain JSC](https://vinbrain.net/vi). The text is in the public domain. Dataset size: `1.28GB`. Total audio duration: `9.5 hours`. ### Text-audio samples - Sample 1: + Audio: [file1](https://huggingface.co/datasets/thotnd/VBSF001/resolve/main/1.wav) + Text: song cũng từ buổi tối bất hạnh ấy, một nỗi buồn ghê gớm xâm chiếm nhà vua và thường xuyên lộ ra nét mặt. - Sample 2: + Audio: [file2](https://huggingface.co/datasets/thotnd/VBSF001/blob/main/2.wav) + Text: theo luật pháp nước nhà, sa-dơ-năng không được chia quyền, đành phải sống như một người dân thường. ### Download Get the dataset from here: [link](https://huggingface.co/datasets/thotnd/VBSF001/blob/main/vbsf001.zip). `VBSF001` directory structure: ``` VBSF001 ├── metadata.csv └── wavs ├── 1.wav ├── 2.wav ├── 3.wav ... ``` ### Statistics - Total Clips: 6,835 - Total Words: 121,423 - Total Characters: 528,088 - Total Duration: 9:32:29 - Mean Clip Duration: 5.03 sec - Min Clip Duration: 0.58 sec - Max Clip Duration: 14.09 sec - Mean Words per Clip: 17.76 - Distinct Words: 3,527	thotnd/VBSF001	[ "license:mit", "region:us" ]	2022-06-22T02:58:28+00:00	{"license": "mit"}	2022-06-22T03:56:08+00:00
97b8ae0025c889f8ca38ff6a5598ac950e102f6d	# Dataset Card for Nexdata/Scene_Noise_Data_by_Voice_Recorder ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/25?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is multi-scene noise data, covering subway, supermarket, restaurant, road, airport, exhibition hall, high-speed rail, highway, city road, cinema and other daily life scenes.The data is recorded by the professional recorder Sony ICD-UX560F, which is collected in a high sampling rate and two-channel format, and the recording is clear and natural. The valid data is 101 hours. For more details, please refer to the link: https://www.nexdata.ai/datasets/25?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Noise Data ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Scene_Noise_Data_by_Voice_Recorder	[ "region:us" ]	2022-06-22T05:18:19+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:36:39+00:00
6aa9bdc5816633cb147275da7a537a9c8e728a65	# Dataset Card for Nexdata/British_English_Average_Tone_Speech_Synthesis_Corpus ## Description 10 People - British English Average Tone Speech Synthesis Corpus. It is recorded by British English native speakers, with authentic accent. The phoneme coverage is balanced. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/1309?source=Huggingface # Specifications ## Format 48,000Hz, 24bit, uncompressed wav, mono channel; ## Recording environment professional recording studio; ## Recording content general narrative sentences, interrogative sentences, etc; ## Speaker british native speaker, 5 male and 5 female, 2 hours per person; ## Device microphone; ## Language British English; ## Annotation word and phoneme transcription, four-level prosodic boundary annotation; ## Application scenarios speech synthesis. # Licensing Information Commercial License	Nexdata/British_English_Average_Tone_Speech_Synthesis_Corpus	[ "task_categories:text-to-speech", "language:en", "region:us" ]	2022-06-22T05:20:42+00:00	{"language": ["en"], "task_categories": ["text-to-speech"]}	2024-01-26T08:47:18+00:00
cc2449b837e6f2ae44102b1dde757a99692b7cbf	# Dataset Card for Nexdata/Mandarin_Spontaneous_Speech_Data ## Description 3,881 hours - Mandarin Spontaneous Speech Data, the content covering multiple subjects. All the speech audio was manually transcribed into text content; speaker identity, gender, and other attribution are also annotated. This dataset can be used for voiceprint recognition model training, corpus construction for machine translation, and algorithm research introduction, etc. For more details, please refer to the link: https://www.nexdata.ai/datasets/1024?source=Huggingface # Specifications ## Format 16kHz, 16bit, wav, mono channel; ## Content Category Interview; Sports; Variety; Course; Entertainment, Service, etc. ## Annotation annotation for the transcription text, speaker identification, gender ## Language Mandarin ## Accuracy at a Sentence Accuracy Rate (SAR) of being no less than 95% ## Application scenarios speech recognition, video caption generation and video content review # Licensing Information Commercial License	Nexdata/Mandarin_Spontaneous_Speech_Data	[ "task_categories:automatic-speech-recognition", "language:zh", "region:us" ]	2022-06-22T05:22:00+00:00	{"language": ["zh"], "task_categories": ["automatic-speech-recognition"]}	2023-11-10T07:29:12+00:00
5f6109c8744a82028e96b7f4acc71c3cc882b800	# Dataset Card for Nexdata/Microphone_Collecting_Radio_Frequency_Noise_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/34?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is collected in 66 rooms, 2-4 point locations in each room. According to the relative position of the sound source and the point, 2-5 sets of data are collected for each point. The valid time is 20 hours. The data is recorded in a wide range and can be used for smart home scene product development. For more details, please refer to the link: https://www.nexdata.ai/datasets/34?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Noise data ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Microphone_Collecting_Radio_Frequency_Noise_Data	[ "region:us" ]	2022-06-22T05:23:39+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:40:13+00:00
672b581dc2ced2395c7ccad3d90c2ec598fabcc4		ITESM/dataset	[ "license:mit", "region:us" ]	2022-06-22T05:25:56+00:00	{"license": "mit"}	2022-06-22T05:25:56+00:00
2b0ef70a8606b22c7aaa0c65545e707645ae7f56	# Dataset Card for Nexdata/Mandarin_Heavy_Accent_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/44?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It collects 2,034 local Chinese from 26 provinces like Henan, Shanxi, Sichuan, Hunan, Fujian, etc. It is mandarin speech data with heavy accent. The recoring contents are finance and economics, entertainment, policy, news, TV, and movies. For more details, please refer to the link: https://www.nexdata.ai/datasets/44?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Mandarin Chinese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mandarin_Heavy_Accent_Speech_Data	[ "region:us" ]	2022-06-22T05:26:29+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:38:08+00:00
057ace99d76ff35f7aeff4e7be36b338240904a1	# Dataset Card for Nexdata/American_Children_Speech_Data_By_Mobile_Phone ## Description The data is recorded by 290 children from the U.S.A, with a balanced male-female ratio. The recorded content of the data mainly comes from children's books and textbooks, which are in line with children's language usage habits. The recording environment is relatively quiet indoors, the text is manually transferred with high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/1197?source=Huggingface # Specifications ## Format 16kHz, 16bit, uncompressed wav, mono channel ## Recording environment quiet indoor environment, without echo ## Recording content (read speech) children's books and textbooks ## Demographics 286 American children, 53% of which are female, all children are 5-12 years old ## Device Android mobile phone, iPhone ## Language American English ## Application scenarios speech recognition; voiceprint recognition. ## Accuracy rate 95% of sentence accuracy # Licensing Information Commercial License	Nexdata/American_Children_Speech_Data_By_Mobile_Phone	[ "task_categories:automatic-speech-recognition", "language:en", "region:us" ]	2022-06-22T05:28:10+00:00	{"language": ["en"], "task_categories": ["automatic-speech-recognition"]}	2024-01-26T08:55:08+00:00
3545aadb50d41d932c8eb3c24653c5ba26567d60	# Dataset Card for Nexdata/Hong_Kong_Cantonese_Average_Tone_Speech_Synthesis_Corpus ## Description 38 People - Hong Kong Cantonese Average Tone Speech Synthesis Corpus, It is recorded by Hong Kong native speakers. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/1201?source=Huggingface # Specifications ## Format 44,100Hz, 16bit, uncompressed wav, mono channel; ## Recording environment quiet indoor environment, low background noise, without echo; ## Recording content news and colloquial sentences; ## Speaker 9 males, 29 females; ## Device microphone; ## Language Cantonese, English; ## Annotation word and phoneme transcription, prosodic boundary annotation; ## Application scenarios speech synthesis. # Licensing Information Commercial License	Nexdata/Hong_Kong_Cantonese_Average_Tone_Speech_Synthesis_Corpus	[ "task_categories:text-to-speech", "region:us" ]	2022-06-22T05:29:49+00:00	{"task_categories": ["text-to-speech"]}	2024-01-26T08:47:24+00:00
03d7878875156b903f56cdc8536d033f6012aa25	# Dataset Card for Nexdata/Chinese_Mandarin_Speech_Synthesis_Corpus-Female_Imitating_Children ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1091?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Female audio data of adults imitating children, 6599 sentences in total and 6.78 hours. It is recorded by Chinese native speakers, with authentic accent and sweet sound. The phoneme coverage is balanced. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/1091?source=Huggingface ### Supported Tasks and Leaderboards tts: The dataset can be used to train a model for Text to Speech (TTS). ### Languages Mandarin Chinese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Mandarin_Speech_Synthesis_Corpus-Female_Imitating_Children	[ "region:us" ]	2022-06-22T05:44:34+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:37:14+00:00
bfa17f3e502b2cd2f347dfb1cd0d013c4f0a782f	# Dataset Card for Nexdata/Sichuan_Dialect_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/52?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It collects 2,507 speakers from Sichuan Basin and is recorded in quiet indoor environment. The recorded content covers customer consultation and text messages in many fields. The average number of repetitions is 1.3 and the average sentence length is 12.5 words. Sichuan natives participate in quality inspection and proofreading to ensure the accuracy of the text transcription. For more details, please refer to the link: https://www.nexdata.ai/datasets/52?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Sichuan Dialect ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Sichuan_Dialect_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T05:47:11+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:41:35+00:00
e5443f357122c90dc204ec0e023d75f2d33e8f97	# Dataset Card for Nexdata/Korean_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/61?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It collects 211 Korean locals and is recorded in quiet indoor environment. 99 females, 112 males. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/61?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Korean ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Korean_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T05:48:33+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:38:49+00:00
a185254e0fb04e252f56eeb14335bcb9e3bfd189	# Dataset Card for Nexdata/Taiwanese_Mandarin_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/64?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data collected 203 Taiwan people, covering Taipei, Kaohsiung, Taichung, Tainan, etc. 137 females, 66 males. It is recorded in quiet indoor environment. It can be used in speech recognition, machine translation, voiceprint recognition model training and algorithm research. For more details, please refer to the link: https://www.nexdata.ai/datasets/64?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Taiwanese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Taiwanese_Mandarin_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T05:56:08+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:39:25+00:00
ca88bae84c4d08e36fd34fd410b17c3f2066627b	# Dataset Card for Nexdata/German_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/66?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data were collected and recorded by 351 German native speakers with authentic accents. Recording devices are mainstream Android phones and iPhones. The recorded text is designed by professional language experts and is rich in content, covering multiple categories such as general purpose, interactive, vehicle-mounted and household commands. The recording environment is quiet and without echo. The texts are manually transcribed with a high accuracy rate. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/66?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages German ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/German_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T05:57:34+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:41:58+00:00
e6d356c67abde4fc8231fd617637d937c8bc9997	# Dataset Card for Nexdata/Italian_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/68?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Italian speech data (guiding) is collected from 351 Italian native speakers and is recorded in quiet environment. The recording is rich in content, covering multiple categories such as in-car scene, smart home, speech assistant. 50 sentences for each speaker. The valid volumn is 9.8 hours. Each sentence is repeated 2.7 times on average. All texts are manual transcribed with high accuray. For more details, please refer to the link: https://www.nexdata.ai/datasets/68?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Italian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Italian_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T05:58:45+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:42:24+00:00
352bb2fd893d83d85c952cc89e7eebeab63145e7	# Dataset Card for Nexdata/Thai_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/70?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Thai speech data (guiding) is collected from 490 Thailand native speakers and is recorded in quiet environment. The recording is rich in content, covering multiple categories such as in-car scene, smart home, speech assistant. 50 sentences for each speaker. The valid volumn is 15 hours. All texts are manual transcribed with high accuray. For more details, please refer to the link: https://www.nexdata.ai/datasets/70?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Thai ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Thai_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T06:02:13+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-30T09:39:48+00:00
9dea94281fb2feb4f425dd2a72201494670455ff	# Dataset Card for Nexdata/British_English_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/81?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This data set contains 349 English speaker's speech data, all of whom are English locals. The recording environment is quiet. The recorded content includes many fields such as car, home, voice assistant, etc. About 50 sentences per person. Valid data is 9.5 hours. All texts are manually transcribed with high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/81?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages British English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/British_English_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T06:03:37+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:34:44+00:00
70699d5e5314ccb9d8e3ad280985b173e2b1ed92	# Dataset Card for Nexdata/Saudi_Arabic_Spontaneous_Speech_Data ## Description 849 Hours - Saudi Arabic Spontaneous Speech Data, the content covering multiple topics. All the speech audio was manually transcribed into text content; speaker identity, gender, and other attribution are also annotated. This dataset can be used for voiceprint recognition model training, corpus construction for machine translation, and algorithm research introduction For more details, please refer to the link: https://www.nexdata.ai/datasets/1150?source=Huggingface # Specifications ## Format 16kHz, 16bit, wav, mono channel; ## Content category including interview, variety show, live, etc. ## Language Arabic; ## Annotation annotation for the transcription text, speaker identification, gender; ## Application scenarios speech recognition, video caption generation and video content review; ## Accuracy at a Sentence Accuracy Rate (SAR) of being no less than 95%. # Licensing Information Commercial License	Nexdata/Saudi_Arabic_Spontaneous_Speech_Data	[ "task_categories:automatic-speech-recognition", "language:ar", "region:us" ]	2022-06-22T06:04:59+00:00	{"language": ["ar"], "task_categories": ["automatic-speech-recognition"]}	2023-11-10T07:29:02+00:00
dffc63b631c2f0b99fcb41d1c77cabde417624c2	# Dataset Card for Nexdata/Korean_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/933?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 357 hours of Korean speech data collected by cellphone. It is recorded by 999 Korean in quiet environment and is rich in content. All texts are transtribed by professional annotator. The accuracy rate of sentence is 95%. It can be used for speech recognition, machine translation and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/933?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Korean ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Korean_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:06:12+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:38:40+00:00
ae504f927091ea9ecbb9b65ef0bf067a17cb4e82	# Dataset Card for Nexdata/Chinese_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/234?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The dataset contains 200 Chinese native speakers, covering main dialect zones. It is recorded in both noisy and quiet environment and more suitable for the actual application scenario for speech recognition. The recordings are commonly used spoken sentences. Texts are transcribed by professional annotators. It can be used for speech recognition and machine translation. For more details, please refer to the link: https://www.nexdata.ai/datasets/234?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:07:28+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:30:14+00:00
55bc73c7be7d3da1667feeda52cd5e5f863cd854	# Dataset Card for Nexdata/In-Car_Noise_Data_by_Microphone_and_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/233?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 531 hours of noise data in in-car scene. It contains various vehicle models, road types, vehicle speed and car windoe close/open condition. Six recording points are placed to record the noise situation at different positions in the vehicle and accurately match the vehicle noise modeling requirements. For more details, please refer to the link: https://www.nexdata.ai/datasets/233?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Noise Data ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/In-Car_Noise_Data_by_Microphone_and_Mobile_Phone	[ "region:us" ]	2022-06-22T06:08:47+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:50:34+00:00
94f7af149d3f81470eb2d9f8e1538c00b7d4d651	# Dataset Card for Nexdata/French_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/114?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data volume is 231 hours and is recorded by 406 speakers (from French, Canada, and Africa). The recording is in quiet environment and rich in content. It contains various fields like economics, entertainment, news, and spoken language. All texts are manually transcribed. The sentence accuracy rate is 95%. For more details, please refer to the link: https://www.nexdata.ai/datasets/114?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages French ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/French_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-22T06:10:09+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:34:19+00:00
8281cda5b3eb1dfb95fc81eb4bd0a77154006477	# Dataset Card for Nexdata/French_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/115?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 401 speakers participate in this recording. 50 sentences for each speaker, total 10.9 hours. Recording texts include in-car scene, smart home, smart speech assistant. Texts are accurate after manually transcribed. Recording devices are mainstream Android phones and iPhones. It can be used for in-car scene, smart home and speech assistant. For more details, please refer to the link: https://www.nexdata.ai/datasets/115?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages French ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/French_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T06:14:24+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:33:56+00:00
022dfe1fc12d3910257552d78fb8a95b708658f5	# Dataset Card for Nexdata/Spanish Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/116?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data volumn is 227 hours. It is recorded by Spanish native speakers from Spain, Mexico and Venezuela. It is recorded in quiet environment. The recording contents cover various fields like economy, entertainment, news and spoken language. All texts are manually transcribed. The sentence accurate is 95%. For more details, please refer to the link: https://www.nexdata.ai/datasets/116?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Spanish_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-22T06:15:59+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:38:11+00:00
a15b155f85414d35b33ece0a334412d2dab3f02d	# Dataset Card for Nexdata/Spanish_Speech_Data_by_Mobile_Phone_Guiding ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/117?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This speech data is collected from 343 Spanish native speakers who from Spain, Mexico and Argentina. 50 sentences for each speaker, total 9.9 hours. The recording environment is quiet. Alltexts are amnually transcribed with high accuracy. Recording devices are mainstream Android phones and iPhones. It can be used for speech recogntion, machine translation and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/117?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Spanish_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T06:17:06+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:36:02+00:00
f2309019941a1beff3a7db8254b13bd9d7cdd64a	# Dataset Card for Nexdata/Hindi_Speech_Data_by_Mobile_Phone_Reading ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/118?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is 240 hours and is recorded by 401 Indian. It is recorded in both quiet and noisy environment, which is more suitable for the actual application scenario. The recording content is rich, covering economic, entertainment, news, spoken language, etc. All texts are manually transferred, with high accuracy. It can be applied to speech recognition, machine translation, voiceprint recognition. For more details, please refer to the link:https://www.nexdata.ai/datasets/118?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Hindi ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Hindi_Speech_Data_by_Mobile_Phone_Reading	[ "region:us" ]	2022-06-22T06:18:11+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-24T09:36:11+00:00
7e20b3bc970d92a41ee4457f94599b2e1a5500c2	# Dataset Card for Nexdata/Hindi_Speech_Data_by_Mobile_Phone_Guidinge ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/119?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is recorded by 397 Indian with authentic accent, 50 sentences for each speaker, total 8.6 hours. The recording content involves car scene, smart home, intelligent voice assistant. This data can be used for corpus construction of machine translation, model training and algorithm research for voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/119?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Hindi ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Hindi_Speech_Data_by_Mobile_Phone_Guiding	[ "region:us" ]	2022-06-22T06:19:25+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-24T09:37:55+00:00
76136ed76ce2829f0bd699d1edba90829558883b	# Dataset Card for Nexdata/Hindi_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/946?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data is 824 hours long and was recorded by 1,500 Indian native speakers. The accent is authentic. The recording text is designed by language experts and covers general, interactive, car, home and other categories. The text is manually proofread, and the accuracy is high. Recording devices are mainstream Android phones and iPhones. It can be applied to speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/946?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Hindi ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Hindi_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:21:03+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-24T09:38:14+00:00
687348d06ac9e48016a922fee8ac177af9da8742	# Dataset Card for Nexdata/Spanish_Speech_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/245?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The 338-hour Spanish speech data and is recorded by 800 Spanish-speaking native speakers from Spain, Mexico, Argentina. The recording enviroment is queit. All texts are manually transcribed.The sentence accuracy rate is 95%. It can be applied to speech recognition, machine translation, voiceprint recognition and so on. For more details, please refer to the link: https://www.nexdata.ai/datasets/245?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Spanish_Speech_Data	[ "region:us" ]	2022-06-22T06:23:10+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:27:56+00:00
eb46118dc1b36368109b70cd0790a7887b6acb8e	# Dataset Card for Nexdata/Chinese_Mandarin_Synthesis_Corpus_Female_Customer_Service ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1149?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 10.1 Hours -Chinese Mandarin Synthesis Corpus-Female, Customer Service, It is recorded by Chinese native speakers, with lively and frindly voice. The phoneme coverage is balanced. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/1149?source=Huggingface ### Supported Tasks and Leaderboards tts: The dataset can be used to train a model for Text to Speech (TTS). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Mandarin_Synthesis_Corpus_Female_Customer_Service	[ "region:us" ]	2022-06-22T06:26:04+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:27:30+00:00
3e1a95cffb330c708e0ab307de1facd34ae9f441	# Dataset Card for Nexdata/Italian_Speech_Data_Collected_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/247?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Italian languageaudio data captured by mobile phone , with total duration of 347 hours. It is recorded by 800 Italian native speakers, balanced in gender is balanced; the recording environment is quiet; all texts are manually transferred with high accuracy. This data set can be applied on automatic speech recognition, machine translation, and sound pattern recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/247?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Italian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Italian_Speech_Data_Collected_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:27:53+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:27:05+00:00
960638408c22f0ac43fdf98667b34966bbab9e8d	# Dataset Card for Nexdata/Chinese_Children_Speech_data_by_Mobile_phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/937?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Mobile phone captured audio data of Chinese children, with total duration of 3,255 hours. 9,780 speakers are children aged 6 to 12, with accent covering seven dialect areas; the recorded text contains common children languages such as essay stories, numbers, and their interactions on cars, at home, and with voice assistants, precisely matching the actual application scenes. All sentences are manually transferred with high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/937?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Children_Speech_data_by_Mobile_phone	[ "region:us" ]	2022-06-22T06:29:25+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:29:45+00:00
0ad88e617410a21f185c495513aa639c94f5b22e	# Dataset Card for Nexdata/Indian_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/940?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Indian English audio data captured by mobile phones, 1,012 hours in total, recorded by 2,100 Indian native speakers. The recorded text is designed by linguistic experts, covering generic, interactive, on-board, home and other categories. The text has been proofread manually with high accuracy; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/940?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Indian English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Indian_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:47:10+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:39:25+00:00
5196ee6606667604aad5cf0341aea28b363b8d29	# Dataset Card for Nexdata/UAE_Arabic_Spontaneous_Speech_Data ## Description The 749 hour UAE Arabic Spontaneous Speech Data, the content covering multiple topics. All the speech audio was manually transcribed into text content; speaker identity, gender, and other attribution are also annotated. This dataset can be used for voiceprint recognition model training, corpus construction for machine translation, and algorithm research introduction For more details, please refer to the link: https://www.nexdata.ai/datasets/1180?source=Huggingface # Specifications ## Format 16kHz, 16bit, mono channel; ## Content category Interview; Speech; Variety, etc. ## Language UAE Arabic; ## Annotation annotation for the transcription text, speaker identification, gender; ## Application scenarios speech recognition, video caption generation and video content review; ## Accuracy at a Sentence Accuracy Rate (SAR) of being no less than 95%. # Licensing Information Commercial License	Nexdata/UAE_Arabic_Spontaneous_Speech_Data	[ "task_categories:automatic-speech-recognition", "language:ar", "region:us" ]	2022-06-22T06:48:27+00:00	{"language": ["ar"], "task_categories": ["automatic-speech-recognition"]}	2023-11-10T07:30:07+00:00
407851c288f9a26e9723cdd4ceee91aad155c630	# Dataset Card for Nexdata/Shanghai_Dialect_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/243?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Audiobook annotated pinyin audio data, with duration of 35 hours; 5 speakers are recorded including 3 males and 2 females; Chinese characters and pinyin are annotated, including the tone of pinyin; this data set can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/243?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification, machine-translation: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Pinyin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Pinyin_Annotation_Speech_Data_of_Audio_Book_Text	[ "region:us" ]	2022-06-22T06:49:59+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:51:51+00:00
435a3627beb5a4298b50051460311e7453bad069	# Dataset Card for Nexdata/Mic-Array_Speech_Data_in_Home_Environment ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/230?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Far-field home audio data captured by mobile phone microphone array, 998 people participate in voice record, with gender ratio of 1:1 between male and female; the recorded text covers multiple application scenes; the data set can be used for voice enhancement and automatic automatic speech recognition in home scenes. For more details, please refer to the link: https://www.nexdata.ai/datasets/230?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mic-Array_Speech_Data_in_Home_Environment	[ "region:us" ]	2022-06-22T06:51:20+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:53:16+00:00
045bf1333daa7cc9ec4809e953cc51fa9e7dc425	# Dataset Card for Nexdata/Japanese_Speech_Data_By_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/947?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 474 Hours-Japanese Speech Data By Mobile Phone were recorded by 1,245 local Japanese speakers with authentic accents; the recorded texts cover general, interactive, car, home and other categories, and are rich in content; the text of the voice data collected by this set of Japanese mobile phones has been manually proofread. High accuracy; match mainstream Android and Apple mobile phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/947?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Japanese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Japanese_Speech_Data_By_Mobile_Phone	[ "region:us" ]	2022-06-22T06:52:35+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T02:32:52+00:00
77cafc116bb191b377b32d2dd153425aa4fc8379	# Dataset Card for Nexdata/American_English_Speech_Synthesis_Corpus-Female ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/935?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Female audio data of American English,. It is recorded by American English native speaker, with authentic accent and sweet sound. The phoneme coverage is balanced. Professional phonetician participates in the annotation. It precisely matches with the research and development needs of the speech synthesis. For more details, please refer to the link: https://www.nexdata.ai/datasets/935?source=Huggingface ### Supported Tasks and Leaderboards tts: The dataset can be used to train a model for Text to Speech (TTS). ### Languages American English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/American_English_Speech_Synthesis_Corpus-Female	[ "region:us" ]	2022-06-22T06:55:03+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T03:23:04+00:00
92d4285f739618e2ff3112ed10d1390680a50a34	# Dataset Card for Nexdata/Scene_Noise_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/178?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Scene noise data, with a duration of 1,297 hours. The data covers multiple scenarios, including subways, supermarkets, restaurants, roads, etc.; audio is recorded using professional recorders, high sampling rate, dual-channel format collection; time and type of non-noise are annotated. this data set can be used for noise modeling. For more details, please refer to the link: https://www.nexdata.ai/datasets/178?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Noise Data ### Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Scene_Noise_Data	[ "region:us" ]	2022-06-22T06:56:34+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:51:03+00:00
418bcc31ec41f7eb730b8795e11b85d7af182194	# Dataset Card for Nexdata/English_Emotional_Speech_Data_by_Microphone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/179?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary English emotional audio data captured by microphone, 20 American native speakers participate in the recording, 2,100 sentences per person; the recorded script covers 10 emotions such as anger, happiness, sadness; the voice is recorded by high-fidelity microphone therefore has high quality; it is used for analytical detection of emotional speech. For more details, please refer to the link: https://www.nexdata.ai/datasets/179?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification, emotion-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/English_Emotional_Speech_Data_by_Microphone	[ "region:us" ]	2022-06-22T06:57:59+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:54:34+00:00
54d1322eecde28608b0cbbd270876f0de5942827	# Dataset Card for Nexdata/Mandarin_Speech_Data_in_Noisy_Environment_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/191?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Spoken Mandarin audio data under noisy environment captured by mobile phone, it is recorded by 203 speakers from all over China, covering all major dialect regions; and a variety of noise scenes such as subways, supermarkets, restaurants, etc., more suitable for real application scenes; it can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/191?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification, noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mandarin_Speech_Data_in_Noisy_Environment_by_Mobile_Phone	[ "region:us" ]	2022-06-22T06:59:26+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:54:09+00:00
ff2777fc92a7a6a292e2d6e5f381481e90570cb6	# Dataset Card for Nexdata/German_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/949?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary German audio data captured by mobile phone, 1,796 hours in total, recorded by 3,442 German native speakers. The recorded text is designed by linguistic experts, covering generic, interactive, on-board, home and other categories. The text has been proofread manually with high accuracy; this data can be used for automatic speech recognition, machine translation, and voiceprint recognition. For more details, please refer to the link: https://www.nexdata.ai/datasets/949?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages German ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/German_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:00:38+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:51:26+00:00
57bebc3e965385c1845953f16e62e3f55ea9d7f2	# Dataset Card for Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/255?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary The data consists of multiple sets of products, each with a different type of microphone arrays. Noise data is collected from real home scenes of the indoor residence of ordinary residents. The data set can be used for tasks such as voice enhancement and automatic speech recognition in a home scene. For more details, please refer to the link: https://www.nexdata.ai/datasets/255?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition,noisy-speech-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Noise Data ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Far-filed_Noise_Speech_Data_in_Home_Environment_by_Mic-Array	[ "region:us" ]	2022-06-22T07:03:31+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:53:41+00:00
f3ae902e93f1e09d642f02fa8dd4c49ab0d292da	# Dataset Card for Nexdata/Japanese_Speech_Datae ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/934?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1006 Japanese native speakers participated in the recording, coming from eastern, western, and Kyushu regions, while the eastern region accounting for the largest proportion. The recording content is rich and all texts have been manually transferred with high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/934?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Japanese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Japanese_Speech_Data	[ "region:us" ]	2022-06-22T07:05:33+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:57:36+00:00
fbf40b235992c6e772f01b6fe5e555208143f205	# Dataset Card for Nexdata/American_English_Spontaneous_Speech_Data ## Description The 1,178-hour American English Spontaneous Speech Data is a collection of speech clips, covering multiple topics. Audio is transcribed into text, and speaker identity and other more attributes are annotated. This data set can be used for voiceprint recognition model training, construction of corpus for machine translation and algorithm research. For more details, please refer to the link: https://www.nexdata.ai/datasets/1115?source=Huggingface # Specifications ## Format 16kHz, 16bit, mono channel; ## Content category including self-media, conversation, live, lecture, variety-show. ## Language American English; ## Annotation annotation for the transcription text, speaker identification, gender; ## Application scenarios speech recognition, video caption generation and video content review; ## Accuracy at a Sentence Accuracy Rate (SAR) of being no less than 95%. # Licensing Information Commercial License	Nexdata/American_English_Spontaneous_Speech_Data	[ "task_categories:automatic-speech-recognition", "language:en", "region:us" ]	2022-06-22T07:07:16+00:00	{"language": ["en"], "task_categories": ["automatic-speech-recognition"]}	2023-11-10T07:29:24+00:00
41b08241e6492a98f87196babed9828ab7fc2e5f	# Dataset Card for Nexdata/Non-Hispanic_Spanish_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/970?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1,630 non-Spanish nationality native Spanish speakers such as Mexicans and Colombians participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, in-vehicle and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/970?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Non-Hispanic_Spanish_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:08:37+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:59:27+00:00
76a1238a2fff1d5b8a5cfd16a49a3022fecba103	# Dataset Card for Nexdata/Emotional_Video_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/977?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1,003 People - Emotional Video Data. The data diversity includes multiple races, multiple indoor scenes, multiple age groups, multiple languages, multiple emotions (11 types of facial emotions, 15 types of inner emotions). For each sentence in each video, emotion types (including facial emotions and inner emotions), start & end time, and text transcription were annotated.This dataset can be used for tasks such as emotion recognition and sentiment analysis. For more details, please refer to the link: https://www.nexdata.ai/datasets/977?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification, sentiment-recognition: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages English, Chinese ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Emotional_Video_Data	[ "region:us" ]	2022-06-22T07:09:51+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:59:50+00:00
2fcd1dac9d2caad93f62e91869d1f59d42b71081	# Dataset Card for Nexdata/Mandarin_Interactive_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/981?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Mandarin home interaction mobile phone language audio data (Far-field home collected audio data subset), with duration of 849 hours, recorded in the real home scene; content focuses on home instructions, functional assistants and wake-up words, specially designed for smart home, more close to data application scenes. For more details, please refer to the link: https://www.nexdata.ai/datasets/981?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mandarin_Interactive_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:13:02+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:57:12+00:00
4cfcbc7f1d04f7d40ca1796ca15a3ee82db61cbb	# Dataset Card for Nexdata/French_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/989?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1089 French native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. The data set can be applied for automatic speech recognition, and machine translation scenes. For more details, please refer to the link: https://www.nexdata.ai/datasets/989?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages French English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/French_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:14:22+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-31T01:31:13+00:00
c74c84bb5b95b99ce6e8f6e6c3e83ab76101c6cb	# Dataset Card for Nexdata/Spanish_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/990?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 891 Spanish native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. The data set can be applied for automatic speech recognition, and machine translation scenes. For more details, please refer to the link: https://www.nexdata.ai/datasets/990?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Spanish English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Spanish_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:16:02+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:56:48+00:00
ccd1bb12ac2b0a445d722369788e599ab7909b74	# Dataset Card for Nexdata/Singaporean_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1045?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary This dataset is recorded by 452 native Singaporean speakers with a balanced gender. It is rich in content and it covers generic command and control;human-machine interaction; smart home command and control;in-car command and control categories. The transcription corpus has been manually proofread to ensure high accuracy. For more details, please refer to the link: https://www.nexdata.ai/datasets/1045?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Singaporean English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Singaporean_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:17:36+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T03:17:28+00:00
aa5bfb4c655749760616b0ce09ba96cf17d9e2b3	# Dataset Card for Nexdata/Australian_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1046?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary It collects 2.956 speakers from Shanghai and is recorded in quiet indoor environment. The recorded content includes multi-domain customer consultation, short messages, numbers, Shanghai POI, etc. The corpus has no repetition and the average sentence length is 12.68 words. Recording devices are mainstream Android phones and iPhones. For more details, please refer to the link: https://www.nexdata.ai/datasets/1046?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Australian English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Australian_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:19:25+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-25T03:19:47+00:00
9a20c993a0eab537b9c0d40fb34d7d8dc7d13ae9	# Dataset Card for Nexdata/Indonesian_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/991?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1285 Indonesian native speakers participated in the recording with authentic accent. The recorded script is designed by linguists and cover a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. The data set can be applied for automatic speech recognition, and machine translation scenes. For more details, please refer to the link: https://www.nexdata.ai/datasets/991?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Indonesian ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Indonesian_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:20:41+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:58:32+00:00
6fbbd53218b7aaf4ed7563b6f61cb0f8b37eb4ad	# 201-People-Infant-Cry-Speech-Data-by-Mobile-Phone ## Description Crying sound of 201 infants and young children aged 0~3 years old, a number of paragraphs from each of them; It provides data support for detecting children's crying sound in smart home projects. For more details, please refer to the link: https://www.nexdata.ai/datasets/998?source=Huggingface ## Format 16kHz, 16bit, uncompressed wav, mono channel ## Recording Environment relatively quiet indoor environment, without echo ## Recording Content infant cry ## Population 201 people; 105 boys, 96 girls; 132 people aged 0~1, 58 people aged 1~2, 11 people aged 2~3 ## Device iPhone, Android mobile phone ## Application scene abnormal voice recognition,smart home # Licensing Information Commercial License	Nexdata/Infant_Cry_Speech_Data_by_Mobile_Phone	[ "task_categories:automatic-speech-recognition", "task_categories:voice-activity-detection", "region:us" ]	2022-06-22T07:21:57+00:00	{"task_categories": ["automatic-speech-recognition", "voice-activity-detection"], "YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2024-01-26T09:44:10+00:00
59f4bca87b641d9fa74fb99832146f24c302e5e3	# Dataset Card for Nexdata/American_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/999?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary 1842 American native speakers participated in the recording with authentic accent. The recorded script is designed by linguists, based on scenes, and cover a wide range of topics including generic, interactive, on-board and home. The text is manually proofread with high accuracy. It matches with mainstream Android and Apple system phones. For more details, please refer to the link: https://www.nexdata.ai/datasets/999?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages American English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/American_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:23:17+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:55:49+00:00
7c4fc4bde54b57c54d736f748fc22178925578b8	# Dataset Card for Nexdata/Chinese_Children_Speaking_English_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1001?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Children read English audio data, covering ages from preschool (3-5 years old) to post-school (6-12 years old) , with children's speech features; content accurately matches children's actual scenes of speaking English. It provides data support for children's smart home, automatic speech recognition and oral assessment in intelligent education scene, . For more details, please refer to the link: https://www.nexdata.ai/datasets/1001?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese English ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Chinese_Children_Speaking_English_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:24:33+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-24T09:37:42+00:00
0910b09a0850ed7ecc8a65035b86647a8b622345	# Dataset Card for Nexdata/Mandarin_Strong_Accent_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1003?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary More than 2,000 Chinese native speakers participated in the recording with equal gender. Speakers are mainly from the southern China, and some of them are from the provinces of northern China with Strong accents. The recording content is rich, covering mobile phone voice assistant interaction, smart home command and control, In-car command and control, numbers and other fields, which is accurately matching the smart home, intelligent car and other practical application scenarios. For more details, please refer to the link: https://www.nexdata.ai/datasets/1003?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mandarin_Strong_Accent_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:25:45+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:58:10+00:00
e6847b0e86454869eff6262ef1f9c1ce0d47acab	# Dataset Card for Nexdata/Korean_Speech_Data ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1008?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Korean audio data with duration of 516 hours, recorded texts include: daily language, various interactive sentences, home commands, on-board commands, etc. Among 1,077 speakers, male and female speakers are 49% and 51%. The duration of each speaker is around half an hour. For more details, please refer to the link: https://www.nexdata.ai/datasets/1008?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Korean ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Korean_Speech_Data	[ "region:us" ]	2022-06-22T07:27:21+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:29:18+00:00
178e835a2a49cc6aa511cb68ee4560f13bb50e55	# Dataset Card for Nexdata/Mandarin_Voiceprint_Recognition_Speech_Data_by_Mobile_Phone ## Table of Contents - [Table of Contents](#table-of-contents) - [Dataset Description](#dataset-description) - [Dataset Summary](#dataset-summary) - [Supported Tasks and Leaderboards](#supported-tasks-and-leaderboards) - [Languages](#languages) - [Dataset Structure](#dataset-structure) - [Data Instances](#data-instances) - [Data Fields](#data-fields) - [Data Splits](#data-splits) - [Dataset Creation](#dataset-creation) - [Curation Rationale](#curation-rationale) - [Source Data](#source-data) - [Annotations](#annotations) - [Personal and Sensitive Information](#personal-and-sensitive-information) - [Considerations for Using the Data](#considerations-for-using-the-data) - [Social Impact of Dataset](#social-impact-of-dataset) - [Discussion of Biases](#discussion-of-biases) - [Other Known Limitations](#other-known-limitations) - [Additional Information](#additional-information) - [Dataset Curators](#dataset-curators) - [Licensing Information](#licensing-information) - [Citation Information](#citation-information) - [Contributions](#contributions) ## Dataset Description - Homepage: https://www.nexdata.ai/datasets/1009?source=Huggingface - Repository: - Paper: - Leaderboard: - Point of Contact: ### Dataset Summary Each person's time span is very long, which can better cover the sound features of a person in different periods and different states. For more details, please refer to the link: https://www.nexdata.ai/datasets/1009?source=Huggingface ### Supported Tasks and Leaderboards automatic-speech-recognition, audio-speaker-identification: The dataset can be used to train a model for Automatic Speech Recognition (ASR). ### Languages Chinese Mandarin ## Dataset Structure ### Data Instances [More Information Needed] ### Data Fields [More Information Needed] ### Data Splits [More Information Needed] ## Dataset Creation ### Curation Rationale [More Information Needed] ### Source Data #### Initial Data Collection and Normalization [More Information Needed] #### Who are the source language producers? [More Information Needed] ### Annotations #### Annotation process [More Information Needed] #### Who are the annotators? [More Information Needed] ### Personal and Sensitive Information [More Information Needed] ## Considerations for Using the Data ### Social Impact of Dataset [More Information Needed] ### Discussion of Biases [More Information Needed] ### Other Known Limitations [More Information Needed] ## Additional Information ### Dataset Curators [More Information Needed] ### Licensing Information Commerical License: https://drive.google.com/file/d/1saDCPm74D4UWfBL17VbkTsZLGfpOQj1J/view?usp=sharing ### Citation Information [More Information Needed] ### Contributions	Nexdata/Mandarin_Voiceprint_Recognition_Speech_Data_by_Mobile_Phone	[ "region:us" ]	2022-06-22T07:28:38+00:00	{"YAML tags": [{"copy-paste the tags obtained with the tagging app": "https://github.com/huggingface/datasets-tagging"}]}	2023-08-28T07:32:14+00:00

Subsets and Splits

No community queries yet

The top public SQL queries from the community will appear here once available.