Geometrically constraint ICA for convolutive mixtures of sound

Mirko Knaak*, Shoko Araki, Shoji Makino

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

12 Citations (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.

Original languageEnglish
Pages (from-to)725-728
Number of pages4
JournalICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
Publication statusPublished - 2003
Externally publishedYes
Event2003 IEEE International Conference on Accoustics, Speech, and Signal Processing - Hong Kong, Hong Kong
Duration: 2003 Apr 62003 Apr 10

ASJC Scopus subject areas

  • Software
  • Signal Processing
  • Electrical and Electronic Engineering


Dive into the research topics of 'Geometrically constraint ICA for convolutive mixtures of sound'. Together they form a unique fingerprint.

Cite this