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Home / Proceedings / Proceedings of the AAAI Conference on Artificial Intelligence

RobuTrans: A Robust Transformer-Based Text-to-Speech Model

February 1, 2023

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Authors

Naihan Li

University of Electronic Science and Techonoloy of China


Yanqing Liu

Microsoft


Yu Wu

Microsoft


Shujie Liu

Microsoft


Sheng Zhao

Microsoft


Ming Liu

University of Electronic Science and Techonoloy of China


DOI:

10.1609/aaai.v34i05.6337


Abstract:

Recently, neural network based speech synthesis has achieved outstanding results, by which the synthesized audios are of excellent quality and naturalness. However, current neural TTS models suffer from the robustness issue, which results in abnormal audios (bad cases) especially for unusual text (unseen context). To build a neural model which can synthesize both natural and stable audios, in this paper, we make a deep analysis of why the previous neural TTS models are not robust, based on which we propose RobuTrans (Robust Transformer), a robust neural TTS model based on Transformer. Comparing to TransformerTTS, our model first converts input texts to linguistic features, including phonemic features and prosodic features, then feed them to the encoder. In the decoder, the encoder-decoder attention is replaced with a duration-based hard attention mechanism, and the causal self-attention is replaced with a "pseudo non-causal attention" mechanism to model the holistic information of the input. Besides, the position embedding is replaced with a 1-D CNN, since it constrains the maximum length of synthesized audio. With these modifications, our model not only fix the robustness problem, but also achieves on parity MOS (4.36) with TransformerTTS (4.37) and Tacotron2 (4.37) on our general set.

Topics: AAAI

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HOW TO CITE:

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu RobuTrans: A Robust Transformer-Based Text-to-Speech Model Proceedings of the AAAI Conference on Artificial Intelligence (2020) 8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu RobuTrans: A Robust Transformer-Based Text-to-Speech Model AAAI 2020, 8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu (2020). RobuTrans: A Robust Transformer-Based Text-to-Speech Model. Proceedings of the AAAI Conference on Artificial Intelligence, 8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. RobuTrans: A Robust Transformer-Based Text-to-Speech Model. Proceedings of the AAAI Conference on Artificial Intelligence 2020 p.8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. 2020. RobuTrans: A Robust Transformer-Based Text-to-Speech Model. "Proceedings of the AAAI Conference on Artificial Intelligence". 8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. (2020) "RobuTrans: A Robust Transformer-Based Text-to-Speech Model", Proceedings of the AAAI Conference on Artificial Intelligence, p.8228-8235

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu, "RobuTrans: A Robust Transformer-Based Text-to-Speech Model", AAAI, p.8228-8235, 2020.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. "RobuTrans: A Robust Transformer-Based Text-to-Speech Model". Proceedings of the AAAI Conference on Artificial Intelligence, 2020, p.8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. "RobuTrans: A Robust Transformer-Based Text-to-Speech Model". Proceedings of the AAAI Conference on Artificial Intelligence, (2020): 8228-8235.

Naihan Li||Yanqing Liu||Yu Wu||Shujie Liu||Sheng Zhao||Ming Liu. RobuTrans: A Robust Transformer-Based Text-to-Speech Model. AAAI[Internet]. 2020[cited 2023]; 8228-8235.


ISSN: 2374-3468


Published by AAAI Press, Palo Alto, California USA
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Artificial Intelligence 1900 Embarcadero Road, Suite
101, Palo Alto, California 94303 All Rights Reserved

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