基于傅立叶分解方法的语音瞬时基频估计

Pushpendra Singh, Amit Singhal, Binish Fatimah
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引用次数: 0

摘要

语音分析和各种语音处理应用使用浊音信号的瞬时基频$(F_{0})$作为主要声学参数。浊音的低频分量占有F0邻域的大部分能量,其谐波较少。本研究提出了一种利用傅立叶分解方法(FDM)从语音语音信号中提取瞬时F0分量的新方法,该方法将语音信号分解为其幅频调制(AM-FM)分量。我们还证明,与文献中可用的其他AM-FM模型相比,由于FDM所需的频带分解特性而获得的这些衍生AM-FM分量为浊音语音提供了最合适的表示。通过与现有基于经验模态分解(EMD)和其他语音相关算法的比较,给出了数值结果,验证了该方法在估计F0方面的充分性。
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Instantaneous Fundamental Frequency Estimation from Speech using Fourier Decomposition Method
Speech analysis and various speech processing applications use instantaneous fundamental frequency $(F_{0})$ of voiced speech signal as a prime acoustic parameter. The low frequency component of the voiced speech possesses most of the energy in F0 neighbourhood and its few harmonics. In this study, a novel approach is proposed to extract the instantaneous F0 component from a voiced speech signal using Fourier decomposition method (FDM), which decomposes the signal into its amplitude-frequency modulated (AM-FM) components. We also demonstrate that these derived AM-FM components, obtained due to desired frequency band decomposition property of FDM, provides the most suitable representation for voiced speech as compared to other AM-FM models available in the literature. Numerical results are presented to validate the adequacy of proposed method in estimating F0, when compared with existing algorithms based on empirical mode decomposition (EMD) and other speech-related algorithms.
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