1. Blind speech dereverberation using multiple microphones Inseon JANG, Seungjin CHOI Intelligent Multimedia Lab Department of Computer Science and Engineering, POSTECH jinsn@postech.ac.kr Seungjin@postech.ac.kr

2. 2 Outline Introduction What is the Reverberant speech ? Previous approaches for Speech dereverberation Blind speech dereverberation using multiple microphones Blind Equalization using multiple microphones – Single Input Multiple Output (SIMO) system Subspace Method Deterministic Method Results

3. 3 What is the Reverberant Speech ? Reverberant speech cf) Noisy speech The degrading component of the case of reverberation is dependent on previous speech data, whereas the degrading component of the case of noise speech is independent of speech.

4. 4 Previous approaches for Speech dereverberation Cepstrum based approach Adaptive microphone array processing Blind Deconvolution Temporal envelope filtering Multi-Microphone sub-band envelope estimation Wavelet transform extrema clustering Maximum-kurtosis subband adaptive filtering Using LP Residual signal Using Probabilistic Models

5. 5 Blind Equalization using multiple microphones – SIMO system (1/2) source signal Impulse response received signal Inverse filter unknown estimated signal

6. 6 Blind Equalization using multiple microphones – SIMO system (2/2) where is the filtering matrix For virtual channel,

7. 7 Subspace Method By orthogonality between the noise and the signal subspace, the column of are orthogonal to any vector in the noise subspace for Subspace-Based Parameter Estimation Scheme Minimization of the quadratic form

8. 8 Deterministic Method (1/2) Cross Relation Approach

9. 9 Deterministic Method (2/2) Channel estimate Equivalently, the channel estimate can be obtained from the singular vector of associated with the smallest singular value

10. 10 Result (1/3) Reverberant signal and Dereverberant signal

11. 11 Result (2/3) Dereverberation using Subspace method Channel length : 654 Test size : 5000 Result MSE : 1.3608e-007

12. 12 Result (3/3) Dereverberation using Deterministic method Channel length : 654 Test size : 1000 Result MSE : 7.7074e-018