HMM-based TTS System Framework

Saly Keo, Soky Kak, Y. Shiga, H. Kato, H. Kawai
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引用次数: 0

Abstract

The research focuses on the use of Hidden Markov Model (HMM) to build Khmer text-to-speech (TTS) system. Although the system is based on HMM statistic model, language specific functions were newly designed and developed to cope with the orthographical and grammatical nature of Khmer, some of which included word segmentation, grapheme to phoneme conversion, definitions of full context labels and question sets. In total four-thousand phonemically-balanced Khmer sentences were read aloud by an adult male speaker of Khmer, which were in turn served for training a model for Khmer TTS. The system has been incorporated into VoiceTra, a multilingual speech-to-speech translation app that has been developed and maintained by NICT. The app is publicly released for mobile devices and available to download in both App store and Google Play store.
基于hmm的TTS系统框架
本研究的重点是利用隐马尔可夫模型(HMM)构建高棉语文本到语音(TTS)系统。虽然该系统基于HMM统计模型,但针对高棉语的正字法和语法特性,新设计和开发了语言特定功能,其中包括分词、字素到音素转换、全上下文标签定义和问题集。一名说高棉语的成年男性大声朗读了总共4000个音素平衡的高棉句子,这些句子反过来又用于训练高棉TTS的模型。该系统已被纳入由NICT开发和维护的多语种语音对语音翻译应用程序VoiceTra。这款应用面向移动设备公开发布,可在app store和Google Play商店下载。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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