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Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation
The Emilia dataset is the first open-source multilingual in-the-wild dataset for speech generation. It contains over 101k hours of high-quality speech data in six languages: Chinese (zh), English (en), Japanese (ja), Korean (ko), German (de), and French (fr) in various speaking styles and their corresponding transcriptions.
Dataset Overview
The Emilia dataset is constructed from a vast collection of speech data sourced from diverse video platforms and podcasts on the Internet, covering various content genres such as talk shows, interviews, debates, sports commentary, and audiobooks. This variety ensures the dataset captures a wide array of real human speaking styles. The initial version of the Emilia dataset includes a total of 101,654 hours of multilingual speech data in six different languages. The table below provides the duration statistics for each language in the dataset.
| Language | Duration (hours) |
|---|---|
| English | 46,828 |
| Chinese | 49,922 |
| German | 1,590 |
| French | 1,381 |
| Japanese | 1,715 |
| Korean | 217 |
Dataset Usage
To use the Emilia dataset, you can download the raw audio files from the provided URL list and use our open-source Emilia-Pipe preprocessing pipeline to preprocess the raw data and rebuild the dataset. Additionally, users can easily use Emilia-Pipe to preprocess their own raw speech data for custom needs. By open-sourcing the Emilia-Pipe code, we aim to enable the speech community to collaborate on large-scale speech generation research.
The Emilia dataset will be structured as follows:
- Speech Data: High-quality audio recordings in .mp3 format.
- Transcriptions: Corresponding text transcriptions for each audio file.
Please note that Emilia doesn't own the copyright of the audios; the copyright remains with the original owners of the video or audio.
Reference
If you use the Emilia dataset or the Emilia-Pipe pipeline, please cite the following papers:
@article{emilia,
title={Emilia: An Extensive, Multilingual, and Diverse Speech Dataset for Large-Scale Speech Generation},
author={He, Haorui and Shang, Zengqiang and Wang, Chaoren and Li, Xuyuan and Gu, Yicheng and Hua, Hua and Liu, Liwei and Yang, Chen and Li, Jiaqi and Shi, Peiyang and Wang, Yuancheng and Chen, Kai and Zhang, Pengyuan and Wu, Zhizheng},
journal={arXiv},
volume={abs/2407.05361}
year={2024}
}
@article{amphion,
title={Amphion: An Open-Source Audio, Music and Speech Generation Toolkit},
author={Zhang, Xueyao and Xue, Liumeng and Gu, Yicheng and Wang, Yuancheng and He, Haorui and Wang, Chaoren and Chen, Xi and Fang, Zihao and Chen, Haopeng and Zhang, Junan and Tang, Tze Ying and Zou, Lexiao and Wang, Mingxuan and Han, Jun and Chen, Kai and Li, Haizhou and Wu, Zhizheng},
journal={arXiv},
volume={abs/2312.09911}
year={2024},
}
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