Nonnegative Matrix Factor 2-D Deconvolution for Blind Single Channel Source Separation

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    Abstract

    We present a novel method for blind separation of instruments in polyphonic music based on a non-negative matrix factor 2-D deconvolution algorithm. Using a model which is convolutive in both time and frequency we factorize a spectrogram representation of music into components corresponding to individual instruments. Based on this factorization we separate the instruments using spectrogram masking. The proposed algorithm has applications in computational auditory scene analysis, music information retrieval, and automatic music transcription.
    Original languageEnglish
    Title of host publicationICA2006 : Source Separation and Independent Component Analysis, International Conference on (ICA)
    Publication date2006
    Publication statusPublished - 2006
    EventSource Separation and Independent Component Analysis, International Conference on (ICA) -
    Duration: 1 Jan 2006 → …

    Conference

    ConferenceSource Separation and Independent Component Analysis, International Conference on (ICA)
    Period01/01/2006 → …

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