| --- |
| 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: 3353221499.0 |
| num_examples: 35000 |
| download_size: 3145534453 |
| dataset_size: 3353221499.0 |
| --- |
| |
| # 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 |
|
|
| ```python |
| from datasets import load_dataset |
| |
| dataset = load_dataset("jspaulsen/esd") |
| ``` |
|
|
| ## Citation |
|
|
| ```bibtex |
| @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} |
| } |
| ``` |
|
|
