size_categories:
- n<1K
dataset_info:
features:
- name: age
dtype: float32
- name: gender
dtype:
class_label:
names:
'0': female
'1': male
- name: emotion
dtype:
class_label:
names:
'0': anger
'1': boredom
'2': disgust
'3': fear
'4': happiness
'5': neutral
'6': sadness
- name: audio
dtype: audio
- name: m1_gender_prediction
dtype:
class_label:
names:
'0': female
'1': male
- name: m2_gender_prediction
dtype:
class_label:
names:
'0': female
'1': male
- name: m1_embedding
sequence: float32
length: 1028
- name: m2_embedding
sequence: float32
length: 1028
- name: emotion_embedding
sequence: float32
length: 1024
- name: m1_correct
dtype:
class_label:
names:
'0': wrong
'1': correct
- name: m2_correct
dtype:
class_label:
names:
'0': wrong
'1': correct
splits:
- name: train
num_bytes: 54231717
num_examples: 535
download_size: 56965550
dataset_size: 54231717
configs:
- config_name: default
data_files:
- split: train
path: data/train-*
Dataset Card for Dataset Name
Dataset Description
About Dataset Emo-DB Database
The EMODB database is the freely available German emotional database. The database is created by the Institute of Communication Science, Technical University, Berlin, Germany. Ten professional speakers (five males and five females) participated in data recording. The database contains a total of 535 utterances. The EMODB database comprises of seven emotions: 1) anger; 2) boredom; 3) anxiety; 4) happiness; 5) sadness; 6) disgust; and 7) neutral. The data was recorded at a 48-kHz sampling rate and then down-sampled to 16-kHz. Additional Information
Original URL: https://www.tu.berlin/en/kw/research/projects/emotional-speech
Every utterance is named according to the same scheme:
Positions 1-2: number of speaker
Positions 3-5: code for text
Position 6: emotion (sorry, letter stands for german emotion word)
Position 7: if there are more than two versions these are numbered a, b, c ....
Example: 03a01Fa.wav is the audio file from Speaker 03 speaking text a01 with the emotion "Freude" (Happiness). Information about the speakers
03 - male, 31 years old
08 - female, 34 years
09 - female, 21 years
10 - male, 32 years
11 - male, 26 years
12 - male, 30 years
13 - female, 32 years
14 - female, 35 years
15 - male, 25 years
16 - female, 31 years