Predicting the Intelligibility of Noisy and Nonlinearly Processed Binaural Speech

Objective speech intelligibility measures are gaining popularity in the development of speech enhancement algorithms and speech processing devices such as hearing aids. Such devices may process the input signals nonlinearly and modify the binaural cues presented to the user. We propose a method for predicting the intelligibility of noisy and nonlinearly processed binaural speech. This prediction is based on the noisy and processed signal as well as a clean speech reference signal. The method is obtained by extending a modified version of the short-time objective intelligibility (STOI) measure with a modified equalization-cancellation (EC) stage. We evaluate the performance of the method by comparing the predictions with measured intelligibility from four listening experiments. These comparisons indicate that the proposed measure can provide accurate predictions of (1) the intelligibility of diotic speech with an accuracy similar to that of the original STOI measure, (2) speech reception thresholds (SRTs) in conditions with a frontal target speaker and a single interferer in the horizontal plane, (3) SRTs in conditions with a frontal target and a single interferer when ideal time frequency segregation (ITFS) is applied to the left and right ears separately, and (4) the advantage of two-microphone beamforming as applied in state-of-the-art hearing aids. A MATLAB implementation of the proposed measure is available online
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