Paper Info
Title
On The Causality Problem In Time-Domain Blind Source Separation And Deconvolution Algorithms
Abstract
Based on a recently presented generic framework for multichannel blind signal processing for convolutive mixtures we investigate in this paper the problem of incorporating acausal delays which are necessary with certain geometric constellations. Starting from a generic update equation which is applicable to blind source separation (BSS), multichannel blind deconvolution (MCBD), and multichannel blind partial deconvolution (MCBPD) for dereverberation of speech signals, two formulations of the natural gradient are derived. It is shown that one expression is applicable to mere causal filters whereas the other one also allows an implementation of noncausal filters. Moreover, proper initialization methods for both cases are given. For the implementation of the aforementioned algorithms cross-relation estimation techniques known from linear prediction are discussed. Based on these results, relationships between traditional MCBD algorithms can be established. Experimental results of different acoustic scenarios show the applicability of the presented algorithms.
Year
DOI
Venue
2005
10.1109/ICASSP.2005.1416270
2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, VOLS 1-5: SPEECH PROCESSING
Keywords
Field
DocType
blind deconvolution,blind source separation,time domain,deconvolution,parameter estimation,reverberation,constellation diagram,signal processing,causality,bss,speech,speech processing,cocktail party problem
Time domain,Speech processing,Pattern recognition,Blind deconvolution,Computer science,Deconvolution,Algorithm,Linear prediction,Artificial intelligence,Initialization,Blind signal separation,Source separation
Conference
ISSN
Citations 
PageRank 
1520-6149
6
1.08
References 
Authors
3
3
Name
Order
Citations
PageRank
R. Aichner1385.64
Herbert Buchner243540.57
W. Kellermann368671.03