语音中不发音成分的识别与重构

W. Bastiaan Kleijn, A. Jefremov, M. Murthi
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引用次数: 2

摘要

通过源-滤波器模型可以很好地描述语音。音源的特性对高质量的重建语音至关重要。我们描述了一个既方便低速率编码又方便信号修改的源模型。源信号通过音高同步帧展开来描述,不同的系数子集对应于所谓的浊音和非浊音分量。即使在语音开始时,为了获得感知上合理的浊音-浊音分解,我们的帧函数适应信号。未发音分量的生成包括用具有相似统计量的随机变量的实现替换相应的系数。现有的正弦和波形插值激励模型与所提出的方法近似。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Identification and reconstruction of the unvoiced component in speech
Speech is well described by a source-filter model. The source properties are critical for good quality reconstructed speech. We describe a source model which facilitates both low-rate coding and signal modification. The source signal is described by means of pitch-synchronous frame expansions, with different subsets of the coefficients corresponding to so-called voiced and unvoiced components. To obtain a perceptually plausible voiced-unvoiced decomposition even at speech onsets, our frame functions adapt to the signal. The generation of the unvoiced component consists of the replacement of the corresponding coefficients with realizations of a random variable with similar statistics. Existing sinusoidal and waveform-interpolation excitation models form approximations to the presented procedure.
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