YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice
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- URL: http://arxiv.org/abs/2112.02418v4
- Date: Sun, 30 Apr 2023 17:46:06 GMT
- Title: YourTTS: Towards Zero-Shot Multi-Speaker TTS and Zero-Shot Voice
Conversion for everyone
- Authors: Edresson Casanova, Julian Weber, Christopher Shulby, Arnaldo Candido
Junior, Eren G\"olge and Moacir Antonelli Ponti
- Abstract summary: YourTTS brings the power of a multilingual approach to the task of zero-shot multi-speaker TTS.
We achieve 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.
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.
- Score: 0.7927630381442314
- License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
- Abstract: 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.
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