Meta Learning Text-to-Speech Synthesis in over 7000 Languages
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| Udgivet i: | arXiv.org (Jun 10, 2024), p. n/a |
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| Hovedforfatter: | |
| Andre forfattere: | , , , , , , |
| Udgivet: |
Cornell University Library, arXiv.org
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| Fag: | |
| Online adgang: | Citation/Abstract Full text outside of ProQuest |
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| 001 | 3066577103 | ||
| 003 | UK-CbPIL | ||
| 022 | |a 2331-8422 | ||
| 035 | |a 3066577103 | ||
| 045 | 0 | |b d20240610 | |
| 100 | 1 | |a Lux, Florian | |
| 245 | 1 | |a Meta Learning Text-to-Speech Synthesis in over 7000 Languages | |
| 260 | |b Cornell University Library, arXiv.org |c Jun 10, 2024 | ||
| 513 | |a Working Paper | ||
| 520 | 3 | |a In this work, we take on the challenging task of building a single text-to-speech synthesis system that is capable of generating speech in over 7000 languages, many of which lack sufficient data for traditional TTS development. By leveraging a novel integration of massively multilingual pretraining and meta learning to approximate language representations, our approach enables zero-shot speech synthesis in languages without any available data. We validate our system's performance through objective measures and human evaluation across a diverse linguistic landscape. By releasing our code and models publicly, we aim to empower communities with limited linguistic resources and foster further innovation in the field of speech technology. | |
| 653 | |a Linguistics | ||
| 653 | |a Learning | ||
| 653 | |a Languages | ||
| 653 | |a Speech recognition | ||
| 700 | 1 | |a Meyer, Sarina | |
| 700 | 1 | |a Behringer, Lyonel | |
| 700 | 1 | |a Zalkow, Frank | |
| 700 | 1 | |a Do, Phat | |
| 700 | 1 | |a Coler, Matt | |
| 700 | 1 | |a Habets, Emanuël A P | |
| 700 | 1 | |a Vu, Ngoc Thang | |
| 773 | 0 | |t arXiv.org |g (Jun 10, 2024), p. n/a | |
| 786 | 0 | |d ProQuest |t Engineering Database | |
| 856 | 4 | 1 | |3 Citation/Abstract |u https://www.proquest.com/docview/3066577103/abstract/embedded/75I98GEZK8WCJMPQ?source=fedsrch |
| 856 | 4 | 0 | |3 Full text outside of ProQuest |u http://arxiv.org/abs/2406.06403 |