Speedup Convergence And Reduce Noise For Enhanced Speech Separation And Recognition

Yunxin Zhao, Rong Hu, and Xiaolong Li

Abstract

Novel techniques are proposed to enhance time-domain adaptive decorrelation filtering (ADF) for separation and recognition of cochannel speech in reverberant room conditions. The enhancement techniques include whitening filtering on cochannel speech to improve condition of adaptive estimation, block-iterative formulation of ADF to speed up convergence, and integration of multiple ADF outputs through post filtering to reduce reverberation noise. Experimental data were generated by convolving TIMIT speech with acoustic path impulse responses measured in real room environment, with approximately 2 m microphone-source distance and initial target-to-interference ratio of about 0 dB. The proposed techniques significantly improved ADF convergence rate, target-to-interference ratio, and accuracy of phone recognition.

Details

Publication typeArticle
Published inIEEE Transactions on Audio, Speech and Language Processing
PublisherInstitute of Electrical and Electronics Engineers, Inc.
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