Removal of residual crosstalk components in blind source separation using LMS filters

R. Mukai, S. Araki, H. Sawada, S. Makino

研究成果: Conference contribution

20 被引用数 (Scopus)

抄録

The performance of blind source separation (BSS) using independent component analysis (ICA) declines significantly in a reverberant environment. The degradation is mainly caused by the residual crosstalk components derived from the reverberation of the jammer signal. This paper describes a post-processing method designed to refine output signals obtained by BSS. We propose a new method which uses LMS filters in the frequency domain to estimate the residual crosstalk components in separated signals. The estimated components are removed by non-stational spectral subtraction. The proposed method removes the residual components precisely, thus it compensates for the weakness of BSS in a reverberant environment. Experimental results using speech signals show that the proposed method improves the signal-to-interference ratio by 3 to 5 dB.

本文言語English
ホスト出版物のタイトルNeural Networks for Signal Processing XII - Proceedings of the 2002 IEEE Signal Processing Society Workshop, NNSP 2002
編集者Samy Bengio, Scott Douglas, Tulay Adali, Jan Larsen, Herve Bourlard
出版社Institute of Electrical and Electronics Engineers Inc.
ページ435-444
ページ数10
ISBN(電子版)0780376161
DOI
出版ステータスPublished - 2002
外部発表はい
イベント12th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002 - Martigny, Switzerland
継続期間: 2002 9 6 → …

出版物シリーズ

名前Neural Networks for Signal Processing - Proceedings of the IEEE Workshop
2002-January

Other

Other12th IEEE Workshop on Neural Networks for Signal Processing, NNSP 2002
国/地域Switzerland
CityMartigny
Period02/9/6 → …

ASJC Scopus subject areas

  • 電子工学および電気工学
  • 人工知能
  • ソフトウェア
  • コンピュータ ネットワークおよび通信
  • 信号処理

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