DocumentCode :
3150726
Title :
Blind source separation and acoustic echo cancellation: A unified framework
Author :
Ikram, Muhammad Z.
Author_Institution :
Syst. & Applic. R&D Center, Texas Instrum., Inc., Dallas, TX, USA
fYear :
2012
fDate :
25-30 March 2012
Firstpage :
1701
Lastpage :
1704
Abstract :
We explore interesting connections between blind source separation (BSS) and acoustic echo cancellation (AEC), and develop a framework where the AEC problem is transformed and solved as a BSS problem. We show that by careful selection of the BSS algorithm the double-talk (DT) problem in AEC is solved without the need to use a DT detector or a step-size controller. Furthermore, the echo cancellation performance is maintained even during single-talk when only the far-end speaker is active. The algorithm converges to the true echo path much faster than the normalized least-mean squares adaptation. Moreover, the proposed algorithm does not require a knowledge of the echo-tail length and is robust against under estimation of the echo-filter length. The simple implementation and fast convergence of the proposed method makes it a suitable candidate for implementation on low-power general purpose DSPs.
Keywords :
acoustic signal processing; blind source separation; echo suppression; least mean squares methods; noise abatement; acoustic echo cancellation; blind source separation; double talk problem; far end speaker; normalized least mean squares adaptation; single talk; true echo path; Convergence; Echo cancellers; Microphones; Robustness; Source separation; Speech; Acoustic Echo Cancellation; Blind signal separation; Double Talk; Impulse Response;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Acoustics, Speech and Signal Processing (ICASSP), 2012 IEEE International Conference on
Conference_Location :
Kyoto
ISSN :
1520-6149
Print_ISBN :
978-1-4673-0045-2
Electronic_ISBN :
1520-6149
Type :
conf
DOI :
10.1109/ICASSP.2012.6288225
Filename :
6288225
Link To Document :
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