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A Clustering Approach for Solving the Spatial Aliasing Problem in Convolutive Blind Source Separation

Mazur, Radoslaw, Phan, Huy, Mertins, Alfred (2015) A Clustering Approach for Solving the Spatial Aliasing Problem in Convolutive Blind Source Separation. In: 20th IEEE International Conference on Digital Signal Processing (DSP 2015). . pp. 679-683. IEEE, Singapore ISBN 978-1-4799-8058-1. (doi:10.1109/ICDSP.2015.7251961) (Access to this publication is currently restricted. You may be able to access a copy if URLs are provided)

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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.

Item Type: Conference or workshop item (Proceeding)
DOI/Identification number: 10.1109/ICDSP.2015.7251961
Uncontrolled keywords: Blind source separation, spatial aliasing, permutation problem, convolutive mixture, frequency-domain ICA
Divisions: Faculties > Sciences > School of Computing
Depositing User: Huy Phan
Date Deposited: 25 Feb 2019 16:49 UTC
Last Modified: 03 Jun 2019 09:28 UTC
Resource URI: https://kar.kent.ac.uk/id/eprint/72686 (The current URI for this page, for reference purposes)
Phan, Huy: https://orcid.org/0000-0003-4096-785X
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