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Shivam Mehta
2023-09-07 08:15:38 +00:00
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@@ -26,7 +26,7 @@ We propose Matcha-TTS, a new approach to non-autoregressive neural TTS, that use
- Sounds highly natural - Sounds highly natural
- Is very fast to synthesise from - Is very fast to synthesise from
Please check out the audio examples below and read our arXiv preprint for more details. Please check out the audio examples below and [read our arXiv preprint][arxiv_link] for more details.
Code and pre-trained models will be made available shortly after the ICASSP deadline. Code and pre-trained models will be made available shortly after the ICASSP deadline.
[shivam_profile]: https://www.kth.se/profile/smehta [shivam_profile]: https://www.kth.se/profile/smehta
@@ -35,6 +35,7 @@ Code and pre-trained models will be made available shortly after the ICASSP dead
[eva_profile]: https://www.kth.se/profile/szekely [eva_profile]: https://www.kth.se/profile/szekely
[gustav_profile]: https://people.kth.se/~ghe/ [gustav_profile]: https://people.kth.se/~ghe/
[this_page]: https://shivammehta25.github.io/Matcha-TTS [this_page]: https://shivammehta25.github.io/Matcha-TTS
[arxiv_link]: https://arxiv.org/abs/2309.03199
[grad_tts_paper]: https://arxiv.org/abs/2105.06337 [grad_tts_paper]: https://arxiv.org/abs/2105.06337
[vits_paper]: https://arxiv.org/abs/2106.06103 [vits_paper]: https://arxiv.org/abs/2106.06103
[fastspeech2_paper]: https://arxiv.org/abs/2006.04558 [fastspeech2_paper]: https://arxiv.org/abs/2006.04558