de Fréin, Ruairí and Rickard, Scott T. and Pearlmutter, Barak A. (2008) Sparse Multichannel Source Localization and Separation. In: 8th International Conference on Mathematics in Signal Processing, 16-18 December 2008, Royal Agricultural College, Cirencester, UK.

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Abstract

The DUET and DESPRIT blind source separation algorithms attempt to recover J sources from I mixtures of these sources, in the interesting case where J > I, with minimal information about the mixing environment or underlying source statistics. We present a semi-blind generalization of the DUET-DESPRIT approach which allows arbitrary placement of the sensors and demixes the sources given the room impulse response. We learn a sparse representation of the mixtures on an over-complete spatial signatures dictionary. We localise and separate the constituent sources via binary masking of a power weighted histogram in location space or in attenuation-delay space. We demonstrate the robustness of this technique using synthetic room experiments.

Item Type:	Conference or Workshop Item (Paper)
Keywords:	Sparse Multichannel Source Localization; blind source separation; algorithms; DUET; DESPRIT;
Academic Unit:	Faculty of Science and Engineering > Research Institutes > Hamilton Institute
Item ID:	10243
Depositing User:	Barak Pearlmutter
Date Deposited:	27 Nov 2018 16:38
Refereed:	Yes
Funders:	Science Foundation Ireland (SFI)
URI:
Use Licence:	This item is available under a Creative Commons Attribution Non Commercial Share Alike Licence (CC BY-NC-SA). Details of this licence are available here

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