This paper describes a predictor for binaural speech intelligibility that computes speech reception thresholds (SRT) without the need to perform subjective listening tests. Although listening tests are considered to be the most reliable indicators of performance, such tests are time consuming and costly. The proposed model computes SRTs in two stages. First, it calculates the binaural advantage. Then, it derives the SRTs based on the computed mutual information of the speech and mixture envelopes. Listening tests were conducted with 13 normal-hearing listeners in 15 spatial configurations, covering one, two, and three babble interferers. The proposed predictor performs as well as the baseline model in predicting the intelligibility of binaural vowel-consonant-vowel signals contaminated by multiple nonstationary babble noise sources. The model is evaluated in anechoic conditions and compared with subjective data as well as with the predictions obtained from a baseline binaural speech intelligibility model.
https://www.aes.org/e-lib/browse.cfm?elib=18561
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