  In the scenario with reverberation, the experience of human-machine
interaction will become worse. In order to solve this problem, many methods for
the dereverberation have emerged. At present, how to update the parameters of
the Kalman filter in the existing dereverberation methods based on multichannel
linear prediction (MCLP) is a challenging task, especially, accurate power
spectral density (PSD) estimation of target speech. In this paper, minimum
variance distortionless response (MVDR) beamformer and MCLP are effectively
fused in the dereverberation, where the PSD of target speech used for Kalman
filter is modified in the MCLP. In order to construct a MVDR beamformer, the
PSD of late reverberation and the PSD of the noise are estimated simultaneously
by the blocking-based PSD estimator. Thus, the PSD of target speech used for
Kalman filter can be obtained by subtracting the PSD of late reverberation and
the PSD of the noise from the PSD of observation signal. Compared to the
reference methods, the proposed method shows an outstanding performance.
