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    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, 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:

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