A simple closed-form solution for overdetermined blind separation of locally sparse quasi-stationary sources

Xiao Fu, Wing Kin Ma

Research output: Chapter in Book/Report/Conference proceedingConference contribution

6 Scopus citations

Abstract

We consider the scenario of an unknown overdetermined instantaneous mixture of quasi-stationary sources. Blind source separation (BSS) under this scenario has drawn much attention, motivated by applications such as speech and audio separation. The ideas in the existing BSS works often focus on exploiting the time-varying statistics characteristics of quasi-stationary sources, through various kinds of formulations and optimization methods. In this paper, we are interested in further assuming that the sources exhibit some form of local sparsity, which is generally satisfied in speech. By exploiting this additional assumption, we show that there is a simple closed-form solution for the BSS problem. Simulation results based on real speech show that the proposed closed-form algorithm is computationally much lower than some existing BSS algorithms, while delivering a promising mean-square-error performance.

Original languageEnglish (US)
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages2409-2412
Number of pages4
DOIs
StatePublished - Oct 23 2012
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: Mar 25 2012Mar 30 2012

Publication series

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

Other

Other2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
CountryJapan
CityKyoto
Period3/25/123/30/12

Keywords

  • blind source separation
  • quasi-stationary sources
  • sparsity

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