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Voiced Speech Analysis by Empirical Mode Decomposition

机译:通过经验模式分解的浊音分析

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Recently Empirical Mode Decomposition has been proposed as a nonlinear tool for the analysis of non stationary data. This paper concerns Empirical Mode Decomposition (EMD) of speech signal into intrinsic oscillatory mode functions IMFs and their spectral analysis. EMD is applied on speech signal, spectrogram of speech and IMFs are analysed. The different modes explored, underline the band-pass structure of IMFs. LPC analysis of the different modes shows that formant frequencies of voiced speech signal are still preserved.
机译:最近已经提出了经验模式分解作为用于分析非静止数据的非线性工具。本文涉及语音信号的经验模式分解(EMD)进入内在振荡模式功能IMF及其光谱分析。 EMD应用于语音信号,分析语音和IMF的谱图。探索的不同模式,强调了IMF的频带通行证结构。不同模式的LPC分析表明仍然保留了浊音语音信号的塑造频率。

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