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改进的基于小波变换的语音活动检测算法
引用本文:高戈,胡瑞敏,李德仁.改进的基于小波变换的语音活动检测算法[J].武汉大学学报(信息科学版),2002,27(1):85-88.
作者姓名:高戈  胡瑞敏  李德仁
作者单位:武汉大学多媒体网络通信工程湖北省重点实验室,武汉市珞喻路129号,430079
基金项目:国家自然科学基金资助项目 ( 4 97710 6 4),国家测绘局测绘科技发展基金资助项目 ( 970 0 9)
摘    要:提出了一种改进的基于小波变换的语音活动检测算法。这种新算法能够在不同的时间和尺度上计算用于语音活动检测的参数,根据这些参数得到稳健的语音活动决策。实验表明,新算法与ITUG.729附录B相比,能够更准确地检测到语音活动,语音活动剪切率大为减少;同时新算法对于不同类型的噪声,即使全局信噪比在10dB以下也具有较好的性能。

关 键 词:小波变换  语音活动检测  算法  语音编码
文章编号:1000-050X(2002)01-0085-04
修稿时间:2002年1月14日

Improved Voice Activity Detector Based on the Wavelet Transform
GAO Ge,HU Ruimin,LI Deren.Improved Voice Activity Detector Based on the Wavelet Transform[J].Geomatics and Information Science of Wuhan University,2002,27(1):85-88.
Authors:GAO Ge  HU Ruimin  LI Deren
Institution:GAO Ge 1 HU Ruimin 1 LI Deren 1
Abstract:Owing to the flexibility of time_frequency resolution of wavelet transform,we present an improved voice activity detector (VAD) based on wavelet transform.Robust parameters in different scale and time resolution are computed for VAD decision,such as silence measure,stability measure of amplitude spectrum between adjacent frames,background noise measure of different frequency band,time_domain stability measure of scale 1. The silence measure is used to detect the existence of silence in the input frame.The stability measure of amplitude spectrum between adjacent frames is adopted to give a rough decision of the detection of stable noise based on the assumption that background noise is stable.If current input frame is noise,the energy of every frequency band is below the average of background noise energy threshold over long time.We divide the signal bandwidth into several scales by wavelet transform,and calculate the background noise measure of different scale.In low scale the input signal changes rapidly,and the variety of short time energy will be removed with long window.We calculate the mean square error of short time energy,and get time_domain stability measure from detail coefficients of scale 1.With these measures,we make the VAD decision. Compared with G.729 Annex B,the authors can detect the voice activity more accurately and reduce the ratio of speech clipping using the new algorithm.And the improved algorithm can achieve robust performance for different background noise,even in serious low signal_to_noise environment about 10dB.
Keywords:voice activity detection  wavelet transform  speech coder  
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