A subband adaptive learning algorithm for microphone array based speech enhancement

Authors:
Dongxia Wang;Fuliang Yin
Affiliations:
School of Electronic and Information Engineering, Dalian University of Technology, Dalian and Information Science and Engineering College, Liaoning Institute of Technology, Jinzhou, Liaoning, Chin ...;School of Electronic and Information Engineering, Dalian University of Technology, Dalian, Liaoning, 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

This paper describes a subband adaptive learning algorithm for enhancing microphone array speech signals degraded by a considerable amount of acoustic background noise. The subband multichannel adaptive learning algorithm is adopted to overcome the drawback of slow convergence as well as high computational complexity, which is associated with full band multichannel adaptive LMS algorithm. Simultaneously, oversampled Cosine-modulated filter banks instead of critical sampling filter banks are used to reduce the aliasing effects of subband itself. Simulations experiments show that in addition to fast convergence speed, the proposed microphone array speech enhancement method based on subband adaptive learning algorithm also exhibits a better noise reduction performance than well-known Generalized Sidelobe Canceller (GSC).