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Principal component analysis of the spectrogram of the speech signal: Interpretation and application to dysarthric speech

机译:语音信号频谱图的主成分分析:解构语音的解释和应用

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The article concerns the interpretation of the principal components of the spectrogram of the speech signal and its application to the description of dysarthric speech. Each principal component is a linear combination of the frame spectra. We show that the first principal component of the spectrogram is closely related to the long-term average spectrum (LTAS) and the second principal component is the difference of two weighted sums of frame spectra reporting open and close vowel frame spectra respectively. We investigate articulation deficits in dysarthric speakers via cues obtained from principal components of the spectrogram of connected speech because long-term average spectra have been claimed to inform about speaker settings of the vocal tract. (C) 2019 Elsevier Ltd. All rights reserved.
机译:这篇文章涉及语音信号的频谱图的主要成分的解释及其在构音语言描述中的应用。每个主要成分都是帧光谱的线性组合。我们表明,频谱图的第一个主要成分与长期平均频谱(LTAS)密切相关,第二个主要成分是分别报告打开和关闭元音帧频谱的帧频谱的两个加权和之差。我们通过从连接语音的声谱图的主要成分中获得的线索来调查在构音障碍性说话者中的发音障碍,因为长期平均频谱已被宣称可以告知说话者的声道设置。 (C)2019 Elsevier Ltd.保留所有权利。

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