Abstract
We tackle the task of text-to-speech (TTS) in Hebrew. Traditional Hebrew contains Diacritics, which dictate the way individuals should pronounce given words, however, modern Hebrew rarely uses them. The lack of diacritics in modern Hebrew results in readers expected to conclude the correct pronunciation and understand which phonemes to use based on the context. This imposes a fundamental challenge on TTS systems to accurately map between text-to-speech. In this work, we propose to adopt a language modeling Diacritics-Free approach, for the task of Hebrew TTS. The model operates on discrete speech representations and is conditioned on a word-piece tokenizer. We optimize the proposed method using in-the-wild weakly supervised data and compare it to several diacritic-based TTS systems. Results suggest the proposed method is superior to the evaluated baselines considering both content preservation and naturalness of the generated speech. Samples can be found under the following link: pages.cs.huji.ac.il/adiyoss-lab/HebTTS/.
Original language | English |
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Pages (from-to) | 2775-2779 |
Number of pages | 5 |
Journal | Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH |
DOIs | |
State | Published - 2024 |
Event | 25th Interspeech Conferece 2024 - Kos Island, Greece Duration: 1 Sep 2024 → 5 Sep 2024 |
Bibliographical note
Publisher Copyright:© 2024 International Speech Communication Association. All rights reserved.
Keywords
- Diacritic
- Hebrew speech
- Text-to-Speech