Nonnegative matrix factor 2-d deconvolution for blind single channel source separation

  • Authors:
  • Mikkel N. Schmidt;Morten Mørup

  • Affiliations:
  • Informatics and Mathematical Modelling, Technical University of Denmark, Kgs. Lyngby, Denmark;Informatics and Mathematical Modelling, Technical University of Denmark, Kgs. Lyngby, Denmark

  • Venue:
  • ICA'06 Proceedings of the 6th international conference on Independent Component Analysis and Blind Signal Separation
  • Year:
  • 2006

Quantified Score

Hi-index 0.00

Visualization

Abstract

We present a novel method for blind separation of instruments in single channel polyphonic music based on a non-negative matrix factor 2-D deconvolution algorithm. The method is an extention of NMFD recently introduced by Smaragdis [1]. 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.