Sebastian Braun, Boaz Schwartz, Sharon Gannot and Emanuel A. P. Habets
Published in the Proc. of the International Workshop on Acoustic Signal Enhancement (IWAENC), 2016.
The estimation accuracy of the late reverberation power spectral density (PSD) is of paramount importance in single-channel frequency-domain dereverberation algorithms. In this domain, the reverberant signal can be modeled by the convolution of an early speech component and a relative convolutive transfer function (RCTF). In this work, the RCTF coefficients are modeled by a first-order Markov chain, which is well-suited to model time-varying scenarios. The RCTF coefficients are estimated online by a Kalman filter and are then used to compute the late reverberation PSD, which is used in a spectral enhancement filter to achieve dereverberation and noise reduction. It is shown that the proposed reverberation PSD estimator yields similar performance to other estimators, which impose a model on the reverberant tail and which depend on additional information like the reverberation time and the direct-to-reverberation ratio.