Solving the permutation problem of frequency-domain BSS when spatial aliasing occurs with wide sensor spacing

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

*この研究の対応する著者

研究成果: Conference contribution

14 被引用数 (Scopus)

抄録

This paper describes a method for solving the permutation problem of frequency-domain blind source separation (BSS). The method analyzes the mixing system information estimated with independent component analysis (ICA). When we use widely spaced sensors or increase the sampling rate, spatial aliasing may occur for high frequencies due to the possibility of multiple cycles in the sensor spacing. In such cases, the estimated information would imply multiple possibilities for a source location. This causes some difficulty when analyzing the information. We propose a new method designed to overcome this difficulty. This method first estimates the model parameters for the mixing system at low frequencies where spatial aliasing does not occur, and then refines the estimations by using data at all frequencies. This refinement leads to precise parameter estimation and therefore precise permutation alignment. Experimental results show the effectiveness of the new method.

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V77-V80
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月 142006 5月 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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