Geometrically constraint ICA for convolutive mixtures of sound

Mirko Knaak*, Shoko Araki, Shoji Makino


研究成果: Conference article査読

12 被引用数 (Scopus)


The goal of this contribution is a new algorithm using independent component analysis with a geometrical constraint. The new algorithm solves the permutation problem of blind source separation of acoustic mixtures, and it is significantly less sensitive to the precision of the geometrical constraint than an adaptive beamformer. A high degree of robustness is very important since the steering vector is always roughly estimated in the reverberant environment, even when the look direction is precise. The new algorithm is based on FastICA and constrained optimization. It is theoretically and experimentally analyzed with respect to the roughness of the steering vector estimation by using impulse responses of real room. The effectiveness of the algorithms for real-world mixtures is also shown in the case of three sources and three microphones.

ジャーナルICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
出版ステータスPublished - 2003
イベント2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
継続期間: 2003 4月 62003 4月 10

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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