A Time-Weighted Method for Predicting the Intelligibility of Speech in the Presence of Interfering Sounds

The speech intelligibility index (SII) has been widely used as an objective method of predicting speech intelligibility, but its traditional form is most effective predicting speech intelligibility scores under stationary noise but not more challenging conditions (e.g., competing noise interference). To address this limitation, the present work extended the SII model to predict the intelligibility of speech in both steady speech-spectral noise (SSN) and dual-talker speech (DTS), by using a time-weighted function that accounted for the relative perceptual importance of vowels and consonants in speech intelligibility. The performance of the new time-weighted SII (TW-SII) was compared to the other two well-known methods, i.e., the time-averaged SII (TA-SII) and coherence SII (CSII). Experimental results showed the intelligibility prediction accuracy of the three methods was similar for speech in SSN, but the prediction by TW-SII was more accurate than those by TA-SII and CSII for speech in DTS. The possible applications and limitations of the present intelligibility model were analyzed and discussed.