DocumentCode
3373450
Title
Geometric source separation: merging convolutive source separation with geometric beamforming
Author
Parra, Lucas ; Alvino, Christopher
Author_Institution
Adaptive Image & Signal Process. Group, Sarnoff Corp., Princeton, NJ, USA
fYear
2001
fDate
2001
Firstpage
273
Lastpage
282
Abstract
Blind source separation of broad band signals in a multi-path environment remains a difficult problem. Robustness has been limited due to frequency permutation ambiguities. Increasing the number of sensors allows improved performance but introduces degrees of freedom in the separating filters that are not determined by separation criteria. We propose to further shape the filters and improve the robustness of blind separation by including geometric information such as sensor positions and localized source assumption. This allows us to combine blind source separation with adaptive and geometric beamforming leading to a number of novel algorithms collectively termed "geometric source separation". Performance comparisons on real room recordings for 2 and 3 simultaneous sources are presented
Keywords
array signal processing; signal sources; blind separation; blind source separation; broad band signals; convolutive source separation; frequency permutation ambiguities; geometric beamforming; geometric information; geometric source separation; localized source assumption; multi-path environment; real room recordings; sensor positions; separation criteria; simultaneous sources; Adaptive signal processing; Array signal processing; Blind source separation; Frequency; Merging; Microphones; Notice of Violation; Robustness; Signal processing algorithms; Source separation;
fLanguage
English
Publisher
ieee
Conference_Titel
Neural Networks for Signal Processing XI, 2001. Proceedings of the 2001 IEEE Signal Processing Society Workshop
Conference_Location
North Falmouth, MA
ISSN
1089-3555
Print_ISBN
0-7803-7196-8
Type
conf
DOI
10.1109/NNSP.2001.943132
Filename
943132
Link To Document