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--- |
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license: cc-by-nc-nd-4.0 |
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task_categories: |
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- automatic-speech-recognition |
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- audio-classification |
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tags: |
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- audio |
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- speech |
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- recognition |
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- emotion |
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- NLP |
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size_categories: |
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- 10K<n<100K |
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--- |
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# Speech Emotion Recognition |
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Dataset comprises **30,000+** audio recordings featuring **4** distinct emotions: euphoria, joy, sadness, and surprise. This extensive collection is designed for research in **emotion recognition**, focusing on the nuances of **emotional speech** and the subtleties of **speech signals** as individuals vocally express their feelings. |
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By utilizing this dataset, researchers and developers can enhance their understanding of **sentiment analysis** and improve **automatic speech processing** techniques. - **[Get the data](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=referral&utm_campaign=speech-emotion-recognition)** |
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Each audio clip reflects the tone, intonation, and emotional expressions of diverse speakers, including various ages, genders, and cultural backgrounds, providing a comprehensive representation of human emotions. The dataset is particularly valuable for developing and testing recognition systems and classification models aimed at detecting emotions in spoken language. |
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# 💵 Buy the Dataset: This is a limited preview of the data. To access the full dataset, please contact us at [https://unidata.pro](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=referral&utm_campaign=speech-emotion-recognition) to discuss your requirements and pricing options. |
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Researchers can leverage this dataset to explore deep learning techniques and develop classification methods that improve the accuracy of emotion detection in real-world applications. The dataset serves as a robust foundation for advancing affective computing and enhancing speech synthesis technologies. |
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# 🌐 [UniData](https://unidata.pro/datasets/speech-emotion-recognition/?utm_source=huggingface&utm_medium=referral&utm_campaign=speech-emotion-recognition) provides high-quality datasets, content moderation, data collection and annotation for your AI/ML projects |