语音信号基音频率估计经验模态分解方法的选频特性研究

A. Alimuradov
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引用次数: 3

摘要

考虑了基音频率估计算法在预处理阶段提高语音信号分析效率的问题。简要回顾了经验模态分解(EMD)方法。互补集成经验模态分解(CEEMD)是语音信号自适应分解的一种新方法。给出了CEEMD的频率选择特性及其在预处理阶段PF估计算法中的应用研究结果。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Research of Frequency-Selective Properties of Empirical Mode Decomposition Methods for Speech Signals' Pitch Frequency Estimation
The problem of efficiency increasing of speech signals' analysis in pitch frequency (PF) estimation algorithms at the pre-processing stage is considered. A brief review of Empirical Mode Decomposition (EMD) methods is presented. The Complementary Ensemble Empirical Mode Decomposition (CEEMD) is offered as a new method of adaptive decomposition of speech signals. The research results of frequency-selective properties of the CEEMD and its application in PF estimation algorithm at the preprocessing stage are provided.
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