Article thumbnail

Directivity-Dependency-Reduced Blind Source Separation Integrating ICA, Beamforming and Binary Masking

By Yoshimitsu Mori, Hiroshi Saruwatari, Kiyohiro Shikano, Takashi Hiekata and Takashi Morita

Abstract

IROS2007: IEEE International Conference on Intelligent Robots and Systems, October 29 - November 2, 2007, San Diego, CA, USA.A real-time two-stage blind source separation (BSS) method for convolutive mixtures of speech is now being studied by the authors, in which a single-input multiple-output (SIMO)-model-based independent component analysis (ICA) and an SIMO-model-based binary masking are combined. However because of using humanoid robot head or directional microphones to observe the sounds and adopting binary masking in the 2nd stage, the previous two-stage BSS method has directivity dependency for sound source layout. In this paper, we introduce an improved BSS method which uses omni-directional microphones and creates flexible directivity internally instead of the fixed directional microphones while keeping the separation performance. The experimental results reveal that the separation performance can be considerably improved by using the proposed method compared with the conventional BSS methods

Publisher: 'Institute of Electrical and Electronics Engineers (IEEE)'
Year: 2007
OAI identifier: oai:library.naist.jp:10061/8178

Suggested articles


To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.