Improving intelligibility prediction under informational masking using an auditory saliency model

Tang, Y and Cox, TJ ORCID: https://orcid.org/0000-0002-4075-7564 2018, Improving intelligibility prediction under informational masking using an auditory saliency model , in: International Conference on Digital Audio Effects, 4-8 September 2018, Aveiro, Portugal.

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Abstract

The reduction of speech intelligibility in noise is usually dominated by energetic masking (EM) and informational masking (IM). Most state-of-the-art objective intelligibility measures (OIM) estimate intelligibility by quantifying EM. Few measures model the effect of IM in detail. In this study, an auditory saliency model, which intends to measure the probability of the sources obtaining auditory attention in a bottom-up process, was integrated into an OIM for improving the performance of intelligibility prediction under IM. While EM is accounted for by the original OIM, IM is assumed to arise from the listener’s attention switching between the target and competing sounds existing in the auditory scene. The performance of the proposed method was evaluated along with three reference OIMs by comparing the model predictions to the listener word recognition rates, for different noise maskers, some of which introduce IM. The results shows that the predictive accuracy of the proposed method is as good as the best reported in the literature. The proposed method, however, provides a physiologically-plausible possibility for both IM and EM modelling.

Item Type: Conference or Workshop Item (Speech)
Schools: Schools > School of Computing, Science and Engineering
Journal or Publication Title: Proceedings of the International Conference on Digital Audio Effects 2018
ISSN: 2413-6700
Funders: Engineering and Physical Sciences Research Council (EPSRC)
Depositing User: Y Tang
Date Deposited: 25 May 2018 13:55
Last Modified: 28 Nov 2019 12:18
URI: http://usir.salford.ac.uk/id/eprint/47113

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