Unsupervised Multiple Source Localization Using Relative Harmonic Coefficients

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    28 Citations (Scopus)

    Abstract

    This paper presents an unsupervised multi-source localization algorithm using a recently introduced feature called the relative harmonic coefficients. We derive a closed-form expression of the feature and briefly summarize its unique properties. We then exploit this feature to develop a single-source frame/bin detector which simplifies the challenging problem of multiple source localization into a single source localization problem. We show that the underlying method is suitable for localization using overlapped, disjoint as well as simultaneous multi-source recordings. Experimental results in both simulated and real-life reverberant environments confirm improved localization accuracy of the proposed method in comparison with the existing state-of-art approach.

    Original languageEnglish
    Title of host publication2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Proceedings
    PublisherInstitute of Electrical and Electronics Engineers Inc.
    Pages571-575
    Number of pages5
    ISBN (Electronic)9781509066315
    DOIs
    Publication statusPublished - May 2020
    Event2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020 - Barcelona, Spain
    Duration: 4 May 20208 May 2020

    Publication series

    NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
    Volume2020-May
    ISSN (Print)1520-6149

    Conference

    Conference2020 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2020
    Country/TerritorySpain
    CityBarcelona
    Period4/05/208/05/20

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