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Application of the Trended Hidden Markov Model to Speech Synthesis

机译:趋势隐马尔可夫模型在语音合成中的应用

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This paper presents our work on a speech synthesis system that utilises the trended Hidden Markov Model to represent the basic synthesis unit. We draw upon both speech recognition and speech synthesis research to develop a system that is able to synthesise intelligible and natural sounding speech. Acoustic units are clustered using the decision tree technique and speech data corresponding to these clusters is used for the training of trended Hidden Markov Model synthesis units. The overall system has been implemented in a PSOLA synthesiser and the resultant speech has been compared with that produced by a conventional diphone synthesiser to yield very encouraging results.
机译:本文介绍了我们在语音合成系统上的工作,该系统利用趋势化的隐马尔可夫模型表示基本合成单元。我们利用语音识别和语音合成研究来开发一种能够合成可理解且自然的语音的系统。使用决策树技术对声学单元进行聚类,并将与这些聚类相对应的语音数据用于训练趋势隐式马尔可夫模型合成单元。整个系统已在PSOLA合成器中实现,并且所得到的语音已与常规双音素合成器产生的语音进行了比较,从而产生了令人鼓舞的结果。

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