Datasets:

jspaulsen
/

esd

license: cc-by-nc-4.0
task_categories:
  - audio-classification
  - automatic-speech-recognition
language:
  - zh
  - en
tags:
  - emotion
  - speech
  - voice
size_categories:
  - 10K<n<100K
configs:
  - config_name: default
    data_files:
      - split: train
        path: data/train-*
dataset_info:
  features:
    - name: audio
      dtype: audio
    - name: transcript
      dtype: string
    - name: emotion
      dtype: string
    - name: speaker_id
      dtype: string
    - name: gender
      dtype: string
    - name: language
      dtype: string
  splits:
    - name: train
      num_bytes: 3353221499
      num_examples: 35000
  download_size: 3145534453
  dataset_size: 3353221499

Emotional Speech Dataset (ESD)

The Emotional Speech Dataset (ESD) is a multilingual emotional speech corpus containing parallel recordings in English and Chinese across 5 emotions.

Dataset Details

Total samples: 35,000
Speakers: 20 (10 Chinese, 10 English)
Emotions: anger, happiness, neutral, sadness, surprise (7,000 each)
Languages: Chinese (zh), English (en) - 17,500 each
Gender: 10 male, 10 female speakers

Dataset Structure

Column	Description
`audio`	Audio waveform (WAV)
`transcript`	Text transcription
`emotion`	anger, happiness, neutral, sadness, surprise
`speaker_id`	Speaker identifier (0001-0020)
`gender`	male / female
`language`	zh (Chinese) / en (English)

Usage

from datasets import load_dataset

dataset = load_dataset("jspaulsen/esd")

Citation

@inproceedings{zhou2021seen,
  title={Seen and unseen emotional style transfer for voice conversion with a new emotional speech dataset},
  author={Zhou, Kun and Sisman, Berrak and Liu, Rui and Li, Haizhou},
  booktitle={ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)},
  pages={920--924},
  year={2021},
  organization={IEEE}
}

@article{zhou2021emotional,
  title={Emotional voice conversion: Theory, databases and ESD},
  journal={Speech Communication},
  volume={137},
  pages={1-18},
  year={2022},
  issn={0167-6393}
}