XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model
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arXiv
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| Format: | Preprint |
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2024
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| _version_ | 1866910476634423296 |
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| author | Casanova, Edresson Davis, Kelly Gölge, Eren Göknar, Görkem Gulea, Iulian Hart, Logan Aljafari, Aya Meyer, Joshua Morais, Reuben Olayemi, Samuel Weber, Julian |
| author_facet | Casanova, Edresson Davis, Kelly Gölge, Eren Göknar, Görkem Gulea, Iulian Hart, Logan Aljafari, Aya Meyer, Joshua Morais, Reuben Olayemi, Samuel Weber, Julian |
| contents | Most Zero-shot Multi-speaker TTS (ZS-TTS) systems support only a single language. Although models like YourTTS, VALL-E X, Mega-TTS 2, and Voicebox explored Multilingual ZS-TTS they are limited to just a few high/medium resource languages, limiting the applications of these models in most of the low/medium resource languages. In this paper, we aim to alleviate this issue by proposing and making publicly available the XTTS system. Our method builds upon the Tortoise model and adds several novel modifications to enable multilingual training, improve voice cloning, and enable faster training and inference. XTTS was trained in 16 languages and achieved state-of-the-art (SOTA) results in most of them. |
| format | Preprint |
| id |
arxiv_https___arxiv_org_abs_2406_04904 |
| institution | arXiv |
| publishDate | 2024 |
| record_format | arxiv |
| spellingShingle | XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model Casanova, Edresson Davis, Kelly Gölge, Eren Göknar, Görkem Gulea, Iulian Hart, Logan Aljafari, Aya Meyer, Joshua Morais, Reuben Olayemi, Samuel Weber, Julian Audio and Speech Processing Computation and Language Sound Most Zero-shot Multi-speaker TTS (ZS-TTS) systems support only a single language. Although models like YourTTS, VALL-E X, Mega-TTS 2, and Voicebox explored Multilingual ZS-TTS they are limited to just a few high/medium resource languages, limiting the applications of these models in most of the low/medium resource languages. In this paper, we aim to alleviate this issue by proposing and making publicly available the XTTS system. Our method builds upon the Tortoise model and adds several novel modifications to enable multilingual training, improve voice cloning, and enable faster training and inference. XTTS was trained in 16 languages and achieved state-of-the-art (SOTA) results in most of them. |
| title | XTTS: a Massively Multilingual Zero-Shot Text-to-Speech Model |
| topic | Audio and Speech Processing Computation and Language Sound |
| url | https://arxiv.org/abs/2406.04904 |