Noise estimate algorithm based on minima controlled GARCH model - 文章详情页

作者：

Meng, X.-B. (Meng, X.-B..) | Bao, C.-C. (Bao, C.-C..) (学者：鲍长春)

收录：

Scopus PKU CSCD

摘要：

Considering　the　problem　that　the　typical　MCRA　(Minima-Controlled　Recursive　Averaging)　noise　estimate　algorithm　fails　to　update　the　power　spectrum　of　noise　effectively　when　the　speech　is　present,　so　this　paper　proposes　a　noise　estimate　algorithm　based　on　minima　controlled　GARCH　model.　The　noise　signal　is　modeled　as　a　GARCH　process　in　time-frequency　domain　and　then　the　proposed　noise　estimate　algorithm　is　achieved　combined　with　the　basis　of　the　framework　of　MCRA　method.　Experimental　and　testing　results　indicate　that　the　proposed　algorithm　can　estimate　the　spectrum　of　noise　more　accurately　compared　with　the　reference　methods.　When　the　proposed　algorithm　is　applied　into　speech　enhancement,　a　better　performance　can　be　achieved　as　well.　©　2016,　Chinese　Institute　of　Electronics.　All　right　reserved.

关键词：

GARCH model; MCRA algorithm; Noise estimate; Speech enhancement

作者机构：

[ 1 ] [Meng, X.-B.]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China
[ 2 ] [Bao, C.-C.]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of Technology, Beijing, 100124, China

通讯作者信息：

鲍长春
[Bao, C.-C.]Speech and Audio Signal Processing Laboratory, School of Electronic Information and Control Engineering, Beijing University of TechnologyChina

电子邮件地址：

chchbao@bjut.edu.cn

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