Letters: Binaural semi-blind dereverberation of noisy convoluted speech signals

Authors:
Jong-Hwan Lee;Sang-Hoon Oh;Soo-Young Lee
Affiliations:
Brain Science Research Center and Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea;Department of Information Communication Engineering, Mokwon University, Daejeon, Republic of Korea;Brain Science Research Center and Department of Bio and Brain Engineering, Korea Advanced Institute of Science and Technology, Daejeon, Republic of Korea
Venue:
Neurocomputing
Year:
2008

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Abstract

In order to overcome a limited performance of a conventional monaural model, this letter proposes a binaural blind dereverberation model. Its learning rule is derived using a blind least-squares measure by exploiting higher-order characteristics of output components. In order to prevent an unwanted whitening of speech signal, we adopt a semi-blind approach by employing a pre-determined whitening filter. The proposed model is evaluated using several simulated conditions and the results show better speech quality than those of the monaural model. The applicability of the model to the real environment is also shown by applying to real-recorded data. Especially, the proposed model attains much improved word error rates from 13.9+/-5.7(%) to 4.1+/-3.5(%) across 13 speakers for testing in the real speech recognition experiments.