Blind source separation of many signals in the frequency domain

Ryo Mukai, Hiroshi Sawada, Shoko Araki, Shoji Makino

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

9 Citations (Scopus)

Abstract

This paper describes the frequency-domain blind source separation (BSS) of convolutively mixed acoustic signals using independent component analysis (ICA). The most critical issue related to frequency domain BSS is the permutation problem. This paper presents two methods for solving this problem. Both methods are based on the clustering of information derived from a separation matrix obtained by ICA. The first method is based on direction of arrival (DOA) clustering. This approach is intuitive and easy to understand. The second method is based on normalized basis vector clustering. This method is less intuitive than the DOA based method, but it has several advantages. First, it does not need sensor array geometry information. Secondly, it can fully utilize the information contained in the separation matrix, since the clustering is performed in high-dimensional space. Experimental results show that our methods realize BSS in various situations such as the separation of many speech signals located in a 3-dimensional space, and the extraction of primary sound sources surrounded by many background interferences.

Original languageEnglish
Title of host publication2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
PagesV969-V972
Publication statusPublished - 2006
Externally publishedYes
Event2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
Duration: 2006 May 142006 May 19

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Volume5
ISSN (Print)1520-6149

Conference

Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
Country/TerritoryFrance
CityToulouse
Period06/5/1406/5/19

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering

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