Late reverberation PSD estimation for single-channel dereverberation using relative convolutive transfer functions

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.

Audio Examples

  • The signals are obtained using measured impulse responses in a room with 630 ms reverberation time. There are two speakers sequentially speaking at two different positions, switching at 9 s.
  • The microphone signal is processed by a Wiener filter using different reverberant PSD estimators.
  • Note that the LRSV estimators use prior knowledge about the reverberation time, whereas the other two estimators don't require this information.