Instrumental and Perceptual Evaluation of Dereverberation Techniques Based on Robust Acoustic Multichannel Equalization

Speech signals recorded in an enclosed space by microphones at a distance from the speaker are often corrupted by reverberation, which arises from the superposition of many delayed and attenuated copies of the source signal. Because reverberation degrades the signal, removing reverberation would enhance quality. Dereverberation techniques based on acoustic multichannel equalization, such as the relaxed multichannel least squares (RMCLS) technique and the partial multichannel equalization technique based on the multiple-input/output inverse theorem (PMINT), are known to be sensitive to room impulse response perturbations. In order to increase their robustness, several methods have been proposed, e.g., using a shorter reshaping filter length, incorporating regularization, or incorporating a sparsity-promoting penalty function. This paper focuses on evaluating the performance of these methods for single-source multi-microphone scenarios, both using instrumental performance measures as well as using subjective listening tests. While commonly used instrumental performance measures indicate that the regularized RMCLS technique yields the largest reverberant energy suppression, subjective listening tests show that the regularized and sparsity-promoting PMINT techniques yield the best perceptual speech quality. By analyzing the correlation between the instrumental and the perceptual results, it is shown that signal-based performance measures are more advantageous than channel-based performance measures to evaluate the perceptual speech quality of signals dereverberated by equalization techniques. Furthermore, this analysis also demonstrates the need to develop more reliable instrumental performance measures.