Sparse Multichannel Source Localization and Separation

de Fréin, Ruairí and Rickard, Scott T. and Pearlmutter, Barak A. (2008) Sparse Multichannel Source Localization and Separation. International Conference on Mathematics in Signal Processing, 8th . The Institute of Mathematics and its Applications, Cirencester, UK.

[thumbnail of rdefreinIMA08.pdf]

Download (3MB) | Preview
[thumbnail of merged.pdf]

Download (3MB) | Preview


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 of underling sources statistics. We present a semi-blind generalization of the DUET-DESCRIPT approach which allows arbitary 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 localize 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: Book
Departments or Groups: Walton Institute for Information and Communications Systems Science
Divisions: School of Science > Department of Computing, Maths and Physics
Depositing User: Ruairi De Frein
Date Deposited: 23 Aug 2016 11:27
Last Modified: 23 Aug 2016 11:27

Actions (login required)

View Item View Item