Abstract

The ideal binary mask (IBM) that was originally defined in anechoic conditions has been found to yield substantial improvements in speech intelligibility in noise. The IBM has recently been extended to reverberant conditions where the direct sound and early reflections of target speech are regarded as the desired signal. It is of great interest to know how the division between early and late reflections impacts on the intelligibility of the IBM-processed noisy reverberant speech. In this present study, the division between early and late reflections in three rooms was first determined by four typical estimation approaches and then used to compute the IBMs in reverberant conditions. The IBMs were then applied to the noisy reverberant mixture signal for segregating the desired signal, and the segregated signal was further presented to normal-hearing listeners for word recognition. Results showed that the IBMs with different divisions between early and late reflections provided substantial improvements in speech intelligibility over the unprocessed mixture signals in all conditions tested, and there were small, but statistically significant, differences in speech intelligibility between the different IBMs in some conditions tested.

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