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Edresson / YourTTS

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YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

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YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone

In our recent paper we propose the YourTTS model. YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker TTS. Our method builds upon the VITS model and adds several novel modifications for zero-shot multi-speaker and multilingual training. We achieved state-of-the-art (SOTA) results in zero-shot multi-speaker TTS and results comparable to SOTA in zero-shot voice conversion on the VCTK dataset. Additionally, our approach achieves promising results in a target language with a single-speaker dataset, opening possibilities for zero-shot multi-speaker TTS and zero-shot voice conversion systems in low-resource languages. Finally, it is possible to fine-tune the YourTTS model with less than 1 minute of speech and achieve state-of-the-art results in voice similarity and with reasonable quality. This is important to allow synthesis for speakers with a very different voice or recording characteristics from those seen during training.

Audios samples

Visit our website for audio samples.

Implementation

All of our experiments were implemented on the Coqui TTS repo.

Colab Demos

Demo URL
Zero-Shot TTS link
Zero-Shot VC link

Checkpoints

All the released checkpoints are licensed under CC BY-NC-ND 4.0

Model URL
Speaker Encoder link
Exp 1. YourTTS-EN(VCTK) link
Exp 1. YourTTS-EN(VCTK) + SCL link
Exp 2. YourTTS-EN(VCTK)-PT link
Exp 2. YourTTS-EN(VCTK)-PT + SCL link
Exp 3. YourTTS-EN(VCTK)-PT-FR link
Exp 3. YourTTS-EN(VCTK)-PT-FR SCL link
Exp 4. YourTTS-EN(VCTK+LibriTTS)-PT-FR SCL link

Results replicability

To insure replicability, we make the audios used to generate the MOS available here. In addition, we provide the MOS for each audio here.

To re-generate our MOS results, follow the instructions here. To predict the test sentences and generate the SECS, please use the Jupyter Notebooks available here.

Test Speakers:

LibriTTS (test clean): 1188, 1995, 260, 1284, 2300, 237, 908, 1580, 121 and 1089

VCTK: p261, p225, p294, p347, p238, p234, p248, p335, p245, p326 and p302

MLS Portuguese: 12710, 5677, 12249, 12287, 9351, 11995, 7925, 3050, 4367 and 13069

Citation


@ARTICLE{2021arXiv211202418C,
  author = {{Casanova}, Edresson and {Weber}, Julian and {Shulby}, Christopher and {Junior}, Arnaldo Candido and {G{\"o}lge}, Eren and {Antonelli Ponti}, Moacir},
  title = "{YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice Conversion for everyone}",
  journal = {arXiv e-prints},
  keywords = {Computer Science - Sound, Computer Science - Computation and Language, Electrical Engineering and Systems Science - Audio and Speech Processing},
  year = 2021,
  month = dec,
  eid = {arXiv:2112.02418},
  pages = {arXiv:2112.02418},
  archivePrefix = {arXiv},
  eprint = {2112.02418},
  primaryClass = {cs.SD},
  adsurl = {https://ui.adsabs.harvard.edu/abs/2021arXiv211202418C},
  adsnote = {Provided by the SAO/NASA Astrophysics Data System}
}

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