Overcomplete Blind Source Separation by Combining ICA and Binary Time-Frequency Masking

Michael Syskind Pedersen, DeLiang Wang, Jan Larsen, Ulrik Kjems

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    Abstract

    A limitation in many source separation tasks is that the number of source signals has to be known in advance. Further, in order to achieve good performance, the number of sources cannot exceed the number of sensors. In many real-world applications these limitations are too strict. We propose a novel method for over-complete blind source separation. Two powerful source separation techniques have been combined, independent component analysis and binary time-frequency masking. Hereby, it is possible to iteratively extract each speech signal from the mixture. By using merely two microphones we can separate up to six mixed speech signals under anechoic conditions. The number of source signals is not assumed to be known in advance. It is also possible to maintain the extracted signals as stereo signals
    Original languageEnglish
    Title of host publicationIEEE International workshop on Machine Learning for Signal Processing
    PublisherIEEE
    Publication date2005
    Pages15-20
    ISBN (Print)0-7803-9517-4
    DOIs
    Publication statusPublished - 2005
    Event2005 IEEE International Workshop on Machine Learning for Signal Processing - Mystic, CT, United States
    Duration: 28 Sep 200530 Sep 2005
    http://mlsp2005.conwiz.dk/

    Workshop

    Workshop2005 IEEE International Workshop on Machine Learning for Signal Processing
    CountryUnited States
    CityMystic, CT
    Period28/09/200530/09/2005
    Internet address

    Bibliographical note

    Copyright: 2005 IEEE. Personal use of this material is permitted. However, permission to reprint/republish this material for advertising or promotional purposes or for creating new collective works for resale or redistribution to servers or lists, or to reuse any copyrighted component of this work in other works must be obtained from the IEEE

    Keywords

    • Overcomplete
    • Time-Frequency (T-F) Masking
    • BSS
    • ICA
    • Underdetermined
    • Blind Source separation

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