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Statistical post-filtering for hidden Markov modeling (HMM)-based speech synthesis

机译:用于基于隐马尔可夫模型(HMM)的语音合成的统计后滤波

摘要

A method and system for improving the quality of speech generated from Hidden Markov Model (HMM)-based Text-To-Speech Synthesizers using statistical post-filtering techniques. An example method involves: (a) determining a scale factor that, when applied to a synthesized reference spectral envelope, minimizes a statistical divergence between a natural reference spectral envelope and the synthesized reference spectral envelope, where the synthesized reference spectral envelope is generated by a state of an HMM; (b) for a given synthesized subject spectral envelope generated by the state of the HMM, determining an enhanced synthesized subject spectral envelope based on the determined scale factor; and (c) generating, by a computing device, a synthetic speech signal including the enhanced synthesized subject spectral envelope.
机译:一种用于使用统计后滤波技术提高从基于隐马尔可夫模型(HMM)的文本到语音合成器生成的语音质量的方法和系统。一种示例方法涉及:(a)确定比例因子,当该比例因子应用于合成参考光谱包络时,它将自然参考光谱包络与合成参考光谱包络之间的统计差异最小化,其中合成参考光谱包络是由HMM的状态; (b)对于由HMM的状态产生的给定的合成对象光谱包络,基于所确定的比例因子确定增强的合成对象光谱包络; (c)通过计算设备生成包括增强的合成主体频谱包络的​​合成语音信号。

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