Blind separation combined frequency invariant beamforming and ICA for far-field broadband acoustic signals

Authors:
Qi Lv;Xianda Zhang;Ying Jia
Affiliations:
Dept. of Automation, Tsinghua University, Beijing, China;Dept. of Automation, Tsinghua University, Beijing, China;Intel China Research Center, Beijing, China
Venue:
ISNN'05 Proceedings of the Second international conference on Advances in neural networks - Volume Part II
Year:
2005

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Abstract

Many famous blind source separation (BSS) in frequency domain have been developed while they can still not avoid the permutation problem. We propose a new BSS approach for far-field broadband acoustic signals via combining the frequency invariant bemforming (FIB) technique and complex-valued independent component analysis (ICA). Compared with other frequency methods, our method can avoid the permutation problem and has much faster convergency rate.We also present a new performance measure to evaluate the separation. Finally, the simulation is given to verify the efficiency of the proposed method.