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In the scenario with reverberation, the experience of human-machineinteraction will become worse. In order to solve this problem, many methods forthe dereverberation have emerged. At present, how to update the parameters ofthe Kalman filter in the existing dereverberation methods based on multichannellinear prediction (MCLP) is a challenging task, especially, accurate powerspectral density (PSD) estimation of target speech. In this paper, minimumvariance distortionless response (MVDR) beamformer and MCLP are effectivelyfused in the dereverberation, where the PSD of target speech used for Kalmanfilter is modified in the MCLP. In order to construct a MVDR beamformer, thePSD of late reverberation and the PSD of the noise are estimated simultaneouslyby the blocking-based PSD estimator. Thus, the PSD of target speech used forKalman filter can be obtained by subtracting the PSD of late reverberation andthe PSD of the noise from the PSD of observation signal. Compared to thereference methods, the proposed method shows an outstanding performance.

An Effective Dereverberation Algorithm by Fusing MVDR and MCLP