EMO / README.md
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---
dataset_info:
features:
- name: speaker_id
dtype: string
- name: emotion
dtype: string
- name: emotion_intensity
dtype: string
- name: transcript
dtype: string
- name: repetition
dtype: string
- name: language
dtype: string
- name: audio
dtype: audio
- name: gender
dtype: string
- name: age
dtype: string
- name: race
dtype: string
- name: ethnicity
dtype: string
splits:
- name: jlcorpus
num_bytes: 448531424.8
num_examples: 2400
- name: ravdess
num_bytes: 592549048.8
num_examples: 1440
- name: enterface
num_bytes: 656498481.817
num_examples: 1287
- name: mead
num_bytes: 2763409133.106
num_examples: 31734
- name: esd
num_bytes: 3267036036.0
num_examples: 35000
- name: cremad
num_bytes: 610714547.78
num_examples: 7442
- name: savee
num_bytes: 59059712.0
num_examples: 480
download_size: 8226860408
dataset_size: 8397798384.3029995
configs:
- config_name: default
data_files:
- split: jlcorpus
path: data/jlcorpus-*
- split: ravdess
path: data/ravdess-*
- split: enterface
path: data/enterface-*
- split: mead
path: data/mead-*
- split: esd
path: data/esd-*
- split: cremad
path: data/cremad-*
- split: savee
path: data/savee-*
---
# Emotion Datasets
This dataset is a collection of several emotion datasets: JL Corpus, RAVDESS, eNTERFACE, MEAD, ESD, and CREMA-D.
Example:
```json
{
"speaker_id": "crema-d-speaker-1067", # Speaker ID
"emotion": "angry", # Emotion label
"emotion_intensity": "medium", # Emotion intensity
"transcript": "It's eleven o'clock.", # Transcript
"repetition": "null", # Repetition
"language": "English", # Language
"audio": "...", # Audio file
"gender": "male", # Gender
"age": "66", # Age group
"race": "Caucasian", # Race
"ethnicity": "Non-Hispanic" # Ethnicity
}
```
## jlcorpus
**Labels**: speaker_id, emotion, transcript, language, gender
**Emotions**: happy, concerned, excited, anxious, assertive, apologetic, angry, neutral, sad, encouraging
**Emotion Intensities**: None
**Languages**: English
**Num unique transcripts: 29**
**Multiple emotions for the same transcript**: Yes
| Transcript | Emotion | Count |
| --- | --- | --- |
| Carl leaps into a jeep. | angry | 16 |
| Carl leaps into a jeep. | anxious | 16 |
| Carl leaps into a jeep. | apologetic | 16 |
| Carl leaps into a jeep. | assertive | 16 |
| Carl leaps into a jeep. | concerned | 16 |
| Carl leaps into a jeep. | encouraging | 16 |
| Carl leaps into a jeep. | excited | 16 |
| ... | ... | ... |
## ravdess
**Labels**: speaker_id, emotion, emotion_intensity, transcript, repetition, language, gender
**Emotions**: angry, happy, disgust, fearful, calm, surprised, neutral, sad
**Emotion Intensities**: strong, normal
**Languages**: English
**Num unique transcripts: 2**
**Multiple emotions for the same transcript**: Yes
| Transcript | Emotion | Emotion Intensity | Count |
| --- | --- | --- | --- |
| Dogs are sitting by the door | angry | normal | 48 |
| Dogs are sitting by the door | angry | strong | 48 |
| Dogs are sitting by the door | calm | normal | 48 |
| Dogs are sitting by the door | calm | strong | 48 |
| Dogs are sitting by the door | disgust | normal | 48 |
| Dogs are sitting by the door | disgust | strong | 48 |
| Dogs are sitting by the door | fearful | normal | 48 |
| ... | ... | ... | ... |
## enterface
**Labels**: speaker_id, emotion, transcript, language
**Emotions**: anger, disgust, fear, happiness, sadness, surprise
**Emotion Intensities**: None
**Languages**: English
**Num unique transcripts: 30**
**Multiple emotions for the same transcript**: No
| Transcript | Emotion | Count |
| --- | --- | --- |
| Aaaaah a cockroach!!! | disgust | 43 |
| Eeeek, this is disgusting!!! | disgust | 43 |
| Everything was so perfect! I just don't understand! | sadness | 43 |
| He (she) was my life. | sadness | 43 |
| I can have you fired you know! | anger | 43 |
| I didn't expect that! | surprise | 43 |
| I don't care about your coffee! Please serve me! | anger | 43 |
| ... | ... | ... |
## mead
**Labels**: speaker_id, emotion, emotion_intensity, language, gender
**Emotions**: contempt, neutral, angry, sad, surprised, fear, happy, disgusted
**Emotion Intensities**: low, medium, high
**Languages**: English
**Multiple emotions for the same transcript**: Unknown
| Emotion | Count |
| --- | --- |
| angry | 4194 |
| contempt | 4215 |
| disgusted | 4284 |
| fear | 4251 |
| happy | 4294 |
| neutral | 1916 |
| sad | 4310 |
| ... | ... |
## esd
**Labels**: speaker_id, emotion, transcript, language
**Emotions**: Happy, Neutral, Surprise, Angry, Sad
**Emotion Intensities**: None
**Languages**: Chinese, English
**Num unique transcripts: 953**
**Multiple emotions for the same transcript**: Yes
| Transcript | Emotion | Count |
| --- | --- | --- |
| A boat put out on the bay. | Angry | 10 |
| A boat put out on the bay. | Happy | 10 |
| A boat put out on the bay. | Neutral | 10 |
| A boat put out on the bay. | Sad | 10 |
| A boat put out on the bay. | Surprise | 10 |
| A deafening chirruping rent the air. | Angry | 10 |
| A deafening chirruping rent the air. | Happy | 10 |
| ... | ... | ... |
## cremad
**Labels**: speaker_id, emotion, emotion_intensity, transcript, language, gender, age, race, ethnicity
**Emotions**: fearful, sad, angry, disgust, happy, neutral
**Emotion Intensities**: null, high, medium, low
**Languages**: English
**Num unique transcripts: 12**
**Multiple emotions for the same transcript**: Yes
| Transcript | Emotion | Emotion Intensity | Count |
| --- | --- | --- | --- |
| Don't forget a jacket. | angry | null | 91 |
| Don't forget a jacket. | disgust | null | 91 |
| Don't forget a jacket. | fearful | null | 91 |
| Don't forget a jacket. | happy | null | 91 |
| Don't forget a jacket. | neutral | null | 91 |
| Don't forget a jacket. | sad | null | 91 |
| I think I have a doctor's appointment. | angry | null | 90 |
| ... | ... | ... | ... |
## savee
**Labels**: gender, transcript, emotion
**Emotions**: anger, disgust, fear, happiness, neutral, sadness, surprise
**Emotion Intensities**: None
**Languages**: Unknown
**Num unique transcripts: 198**
**Multiple emotions for the same transcript**: Yes
| Transcript | Emotion | Count |
| --- | --- | --- |
| A few years later, the dome fell in. | anger | 4 |
| A lot of people were roaming the streets in costumes and masks and having a ball. | anger | 1 |
| A lot of people will roam the streets in costumes and masks and having a ball. | anger | 2 |
| Agricultural products are unevenly distributed. | neutral | 4 |
| Allow Levy here, but rationalise all errors. | neutral | 1 |
| Allow leeway here, but rationalise all errors. | neutral | 3 |
| American newspaper reviewers like to call his plays nihilistic. | sadness | 3 |
| ... | ... | ... |