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Voiced Speech Analysis by Empirical Mode Decomposition

机译:基于经验模态分解的语音分析

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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,经验模态分解已被提出作为一种用于分析非平稳数据的非线性工具。本文涉及将语音信号转换为固有振荡模式函数IMF的经验模式分解(EMD)及其频谱分析。将EMD应用于语音信号,分析语音频谱图和IMF。探索了不同的模式,突显了IMF的带通结构。对不同模式的LPC分析表明,浊音信号的共振峰频率仍被保留。

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