This paper presents a system aiming at joint dereverberation and noise reduction by applying a combination of a beamformer with a single-channel spectral enhancement scheme. First, a minimum variance distortionless response beamformer with an online estimated noise coherence matrix is used to suppress noise and reverberation. The output of this beamformer is then processed by a single-channel spectral enhancement scheme, based on statistical room acoustics, minimum statistics, and temporal cepstrum smoothing, to suppress residual noise and reverberation. The evaluation is conducted using the REVERB challenge corpus, designed to evaluate speech enhancement algorithms in the presence of both reverberation and noise. The proposed system is evaluated using instrumental speech quality measures, the performance of an automatic speech recognition system, and a subjective evaluation of the speech quality based on a MUSHRA test. The performance achieved by beamforming, single-channel spectral enhancement, and their combination are compared, and experimental results show that the proposed system is effective in suppressing both reverberation and noise while improving the speech quality. The achieved improvements are particularly significant in conditions with high reverberation times

Perceptual measures are usually considered more reliable than instrumental measures for evaluating the perceived level of reverberation. However, such measures are costly in both time and money, and, due to variations in stimuli or assessors, the resulting data is not always statistically significant. Therefore, an efficient perceptual measure of the perceived level of reverberation is needed. We compare the use of a multiple stimuli test with the use of pairwise comparison for the evaluation of the perceived level of reverberation. The results suggest that using multiple stimuli is preferable to pairwise comparison as long as the number of conditions to be compared is not too large. Additionally, we use the results from the conducted perceptual measurements to examine the reliability of existing instrumental measures of the perceived level of reverberation. Our observations show which instrumental measures are effective in highlighting differences between RIR characteristics and which ones have to be preferred if one aims at predicting the level of reverberation perceived by a human assessor

This is a repository copy of Non-intrusive speech quality prediction using modulation energies and LSTM-network.

This paper reports on the evaluation of several objective quality measures for predicting the quality of the dereverberated speech signals. The correlations between subjective quality assessment for single-channel dereverberation techniques and objective speech quality as well as speech intelligibility measures are analyzed and discussed. Six different single-channel dereverberation algorithms were included in the evaluation to account for different types of distortions. The subjective quality was assessed along the four attributes reverberant, colored, distorted and overall quality following the recommendations of ITU-T P.835. The objective measures included system-based, i.e. channel-based, as well as signal-based measures