Robust speech dereverberation using subband multichannel least squares with variable relaxation

Multichannel equalization algorithms which are robust to system identification errors (SIEs) are important for practical speech dereverberation. We present an equalizer employing variable relaxation within the framework of the relaxed multichannel least squares (RMCLS) algorithm in frequency subbands. We show that varying the relaxation of constraints in RMCLS leads to a trade-off between robustness to SIEs and improved suppression of the early reflections that can be useful to achieve improved overall perceived speech quality after dereverberation processing. We then develop a method of controlling the amount of relaxation based on the expected level of SIE in each subband. Additionally, our algorithm guarantees robustness even in the presence of very high SIEs by backing off dereverberation in the relevant subbands.