Predicting the intelligibility of noise-corrupted speech non-intrusively by across-band envelope correlation

Recent psychoacoustic studies found that across-band envelope correlation (ABEC) carried important information for speech intelligibility. This motivated the present work to propose an ABEC-based intelligibility measure that could be used to non-intrusively predict speech intelligibility in noise using only temporal envelope waveforms extracted from the noise-corrupted speech. The proposed ABEC-based metric (denoted as ABECm) was computed by averaging the correlation coefficients of mean-removed envelope waveforms from adjacent frequency bands of the noise-corrupted speech. The ABECm measures were evaluated with intelligibility scores obtained from normal-hearing listeners presented with sentences corrupted by four types of maskers in a total of 22 conditions. High correlation (r = 0.96) was obtained between ABECm values and listeners' sentence recognition scores, and this correlation was comparable to those computed with existing intrusive and non-intrusive intelligibility measures. This suggests that across-band envelope correlation may work as a simple but efficient predictor of speech intelligibility in noise, whose computation does not need access to the clean reference signal.