Sparse Multichannel Source Localization and Separation

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, 10 Dec. 2015, IMA (The Institute of Mathematics and its Applications, 2008), Cirencester, UK.

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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: Conference or Workshop Item (Paper)
Additional Information: 10.13140/RG.2.1.3829.6405
Uncontrolled Keywords: Blind Source Separation, Time Frequency Analysis, Localization; Fourier Analysis; Short Time Fourier Transform; Dictionary Learning.
Departments or Groups: Telecommunications Software and Systems Group
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

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