DocumentCode :
2186058
Title :
A clustering approach for solving the spatial aliasing problem in convolutive blind source separation
Author :
Mazur, Radoslaw ; Phan, Huy ; Mertins, Alfred
Author_Institution :
Institute for Signal Processing, University of Lübeck, Ratzeburger Allee 160, 23562, Germany
fYear :
2015
fDate :
21-24 July 2015
Firstpage :
679
Lastpage :
683
Abstract :
In this paper we propose to extend a recently introduced clustering approach for solving the permutation ambiguity in convolutive blind source separation to a case where spatial aliasing occurs. A well known approach for separation of sources is the transformation to the time-frequency domain, where the task can be reduced to multiple instantaneous problems. While these may be easily solved using independent component analysis, this approach has the drawback of the inherent permutation and scaling ambiguities, which have to be corrected before the transformation to the time domain or otherwise the whole process will fail. Here, we extend an existing clustering approach to cope with the case where spatial aliasing occurs. This is achieved by exploiting the direction information of whole clusters instead of single bins. The performance of the proposed method is evaluated on real-room recordings.
Keywords :
Blind source separation; Clustering algorithms; Correlation; Robustness; Speech; Speech processing; Blind source separation; convolutive mixture; frequency-domain ICA; permutation problem; spatial aliasing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Digital Signal Processing (DSP), 2015 IEEE International Conference on
Conference_Location :
Singapore, Singapore
Type :
conf
DOI :
10.1109/ICDSP.2015.7251961
Filename :
7251961
Link To Document :
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