汉语端到端语音合成中韵律短语的实现

Yanfeng Lu, M. Dong, Ying Chen
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引用次数: 25

摘要

文本转语音(TTS)系统近年来发展迅速。利用深度神经网络强大的建模能力,研究人员已经实现了从原始文本到语音的端到端转换。各种研究项目表明,端到端的TTS系统能够生成听起来像英语和其他语言的人声的语音。然而,对于像汉语这样的语言,有两个问题需要处理。首先,由于字符集很大,端到端解决方案需要一个与英文字符集相当的小输入集。其次,端到端方法在汉语中存在严重的韵律错误。在本文中,我们将提出一个基于Tacotron 2和Wavenet声码器的端到端中文TTS系统的解决方案。然后,我们将添加额外的上下文信息来提高韵律短语的表现。我们的实验证明了这一建议的有效性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Implementing Prosodic Phrasing in Chinese End-to-end Speech Synthesis
Text-to-Speech (TTS) systems have been evolving rapidly in recent years. With the great modelling power of deep neural networks, researchers have achieved end-to-end conversion from raw text to speech. It has been shown by various research projects that end-to-end TTS systems are able to generate speech that sounds akin to human voice for English and other languages. However, for languages like Chinese, there are two problems to deal with. Firstly, due to the large character set, a small input set comparable to the English character set is needed for the end-to-end solution. Secondly, there are serious prosodic phrasing mistakes when the end-to-end method is applied to Chinese. In this paper, we will propose a solution for an end-to-end Chinese TTS system on the basis of Tacotron 2 and Wavenet vocoder. We will then add extra contextual information to improve the performance of prosodic phrasing. Our experiments have demonstrated the effectiveness of this proposal.
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