Blind source separation of many signals in the frequency domain

Ryo Mukai*, Hiroshi Sawada, Shoko Araki, Shoji Makino

*この研究の対応する著者

研究成果: Conference contribution

9 被引用数 (Scopus)

抄録

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.

本文言語English
ホスト出版物のタイトル2006 IEEE International Conference on Acoustics, Speech, and Signal Processing - Proceedings
ページV969-V972
出版ステータスPublished - 2006
外部発表はい
イベント2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006 - Toulouse, France
継続期間: 2006 5 142006 5 19

出版物シリーズ

名前ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
5
ISSN(印刷版)1520-6149

Conference

Conference2006 IEEE International Conference on Acoustics, Speech and Signal Processing, ICASSP 2006
国/地域France
CityToulouse
Period06/5/1406/5/19

ASJC Scopus subject areas

  • ソフトウェア
  • 信号処理
  • 電子工学および電気工学

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