%0 Journal Article
%T An Order Statistics Filtering-based Real-time Voice Activity Detection Algorithm<br>基于顺序统计滤波的实时语音端点检测算法
%A GUO Li-Hui
%A HE Xin
%A ZHANG Ya-Xin
%A LV Yue
%A <br>郭丽惠
%A 何昕
%A 张亚昕
%A 吕岳
%J 自动化学报
%D 2008
%I 
%X In this paper,we propose an effective real-time voice activity detection algorithm.It makes use of the subband spectral entropy as the speech/noise discrimination feature.The speech spectrum is divided into several subbands at first. Then,the spectral entropy of each subband is estimated.We apply order statistics filters(OSF)to a sequence of the subband entropies to obtain the spectral entropy of each frame.The speech/noise classification is based on the spectral entropy.The experimental results show that the proposed algorithm can distinguish speech from noise effectively and improve the performance of automatic speech recognition(ASR)system significantly.It is proved to be robust under various noisy environments and SNR conditions.Moreover,the proposed algorithm is of low computational complexity which is suitable for embedded ASR system application.
%K Voice activity detection
%K order statistics filtering
%K subband spectrum entropy
%K speech recognition<br>语音端点检测
%K 顺序统计滤波
%K 子带频谱熵
%K 语音识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=E76622685B64B2AA896A7F777B64EB3A&aid=A4AC50CE44DEE69B1D2D2EC4F8C80FF4&yid=67289AFF6305E306&vid=339D79302DF62549&iid=E158A972A605785F&sid=A4E67967A1AB25F0&eid=F10601728A1E9BEA&journal_id=0254-4156&journal_name=自动化学报&referenced_num=1&reference_num=11