Blind source separation for moving speech signals using blockwise ICA and residual crosstalk subtraction

Ryo Mukai, Hiroshi Sawada, Shoko Arakt, Shoji Makino

Research output: Contribution to journalArticlepeer-review

29 Citations (Scopus)

Abstract

This paper describes a real-time blind source separation (BSS) method for moving speech signals in a room. Our method employs frequency domain independent component analysis (ICA) using a blockwise batch algorithm in the first stage, and the separated signals are refined by postprocessing using crosstalk component estimation and non-stationary spectral subtraction in the second stage. The blockwise batch algorithm achieves better performance than an online algorithm when sources are fixed, and the postprocessing compensates for performance degradation caused by source movement. Experimental results using speech signals recorded in a real room show that the proposed method realizes robust real-time separation for moving sources. Our method is implemented on a standard PC and works in realtime.

Original languageEnglish
Pages (from-to)1941-1948
Number of pages8
JournalIEICE Transactions on Fundamentals of Electronics, Communications and Computer Sciences
VolumeE87-A
Issue number8
Publication statusPublished - 2004 Aug
Externally publishedYes

Keywords

  • Blind source separation
  • Convolutive mixtures
  • Independent component analysis
  • Post processing
  • Realtime
  • Spectral subtraction

ASJC Scopus subject areas

  • Signal Processing
  • Computer Graphics and Computer-Aided Design
  • Electrical and Electronic Engineering
  • Applied Mathematics

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