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High‐speed blind speech separation using FICS method
Author(s) -
Mahdikhani Mahdi,
Kahaei Mohammad Hossein
Publication year - 2014
Publication title -
ieej transactions on electrical and electronic engineering
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.254
H-Index - 30
eISSN - 1931-4981
pISSN - 1931-4973
DOI - 10.1002/tee.21975
Subject(s) - fastica , separation (statistics) , independent component analysis , computer science , blind signal separation , separation method , computation , source separation , speech recognition , algorithm , artificial intelligence , channel (broadcasting) , machine learning , telecommunications , chromatography , chemistry
In this paper, we introduce the fusion of iterative and closed‐form separation ( FICS ) method for high‐speed separation of mixed speech signals. This method is performed in two stages: (i) iterative‐form separation and (ii) closed‐form separation. This algorithm significantly improves the separation quality simply by incorporating only some specific frequency bins into computations. We apply the FICS method to the frequency‐domain independent component analysis ( ICA ) to evaluate its performance in increasing the signal separation speed. Simulation results show that for speech signals, the proposed algorithm is on average 40 times faster than the ICA , while preserving the separation quality. Also, it outperforms the FastICA, JADE , and SOBI in terms of separation quality. © 2014 Institute of Electrical Engineers of Japan. Published by John Wiley & Sons, Inc.