Time-Domain Blind Audio Source Separation using Advanced ICA Methods

被引：0
|
作者：
Koldovsky, Zbynek [1 ]
Tichavsky, Petr [2 ]
机构：
[1] Tech Univ Liberec, Inst Informat Technol & Elect, Liberec, Czech Republic
[2] Acad Sci Czech Republ, Inst Informat Theory & Automat, Prague, Czech Republic
来源：
INTERSPEECH 2007: 8TH ANNUAL CONFERENCE OF THE INTERNATIONAL SPEECH COMMUNICATION ASSOCIATION, VOLS 1-4 | 2007年
关键词：
independent component analysis; multichannel blind deconvolution; audio source separation;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this paper, a prototype of novel algorithm for blind separation of convolutive mixtures of audio sources is proposed. The method works in time-domain, and it is based on the recently very successful algorithm EFICA for Independent Component Analysis, which is an enhanced version of more famous FastICA. Performance of the new algorithm is very promising, at least, comparable to other (mostly frequency domain) algorithms. Audio separation examples are included.
引用
收藏
页码：1861 / +
页数：2
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