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arXiv · 1911.04111

A unified sequence-to-sequence front-end model for Mandarin text-to-speech synthesis

Junjie Pan·Xiang Yin·Zhiling Zhang·Shichao Liu·Yang Zhang·Zejun Ma·Yuxuan Wang
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Abstract

In Mandarin text-to-speech (TTS) system, the front-end text processing module significantly influences the intelligibility and naturalness of synthesized speech. Building a typical pipeline-based front-end which consists of multiple individual components requires extensive efforts. In this paper, we proposed a unified sequence-to-sequence front-end model for Mandarin TTS that converts raw texts to linguistic features directly. Compared to the pipeline-based front-end, our unified front-end can achieve comparable performance in polyphone disambiguation and prosody word prediction, and improve intonation phrase prediction by 0.0738 in F1 score. We also implemented the unified front-end with Tacotron and WaveRNN to build a Mandarin TTS system. The synthesized speech by that got a comparable MOS (4.38) with the pipeline-based front-end (4.37) and close to human recordings (4.49).

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Junjie Pan, Xiang Yin, Zhiling Zhang, Shichao Liu, Yang Zhang, Zejun Ma, Yuxuan Wang. 2019-11-11. A unified sequence-to-sequence front-end model for Mandarin text-to-speech synthesis. https://arxiv.org/abs/1911.04111

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