复解析小波变换与语音信号包络提取和分析

Complex Analytical Wavelet Transform for the Extraction and Analysis of Speech Signal Envelops

利用传统的Ｈｉｌｂｅｒｔ变换方法提取语音信号包络存在一些固有缺陷，为此本文建议了一种复解析小波变换包络提取新方法．该方法将Ｈｉｌｂｅｒｔ分析与小波分析紧密地结合在一起．文中推导并论述了新包络滤波器的时域、频域构造条件和设计方法，选择Ｍｏｒｌｅｔ复小波对语音信号进行了初步数字仿真实验，结果证实了理论分析的正确性，并显示出文中提出的新的分析方法对于信号处理具有许多独特优势和潜在性能．

The traditional Hilbert Transform (HT) used in extracting and analyzing the envelop of speech signal suffers from some drawbacks,for example,unexpected blurs will appear in the extracted envelops which cause a lot of difficulties in the postprocessing of the speech signal.To overcome these draw backs a novel approach CAWT (Complex Analytical Wavelet Transform) for extracting and analyzing speech signal envelops is proposed in the present paper.The CAWT algorithm together with some simulation results are given which show many advantages over the HT extraction method.It is expected that the CAWT will be helpful in the Chinese speech recognition.