A context-based model to predict the intelligibility of sentences in non-stationary noises

Jelmer van Schoonhoven, Koenraad S. Rhebergen*, Wouter A. Dreschler

*Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The context-based Extended Speech Transmission Index (cESTI) (van Schoonhoven et al., 2022, J. Acoust. Soc. Am. 151, 1404-1415) was successfully applied to predict the intelligibility of monosyllabic words with different degrees of context in interrupted noise. The current study aimed to use the same model for the prediction of sentence intelligibility in different types of non-stationary noise. The necessary context factors and transfer functions were based on values found in existing literature. The cESTI performed similar to or better than the original ESTI when noise had speech-like characteristics. We hypothesize that the remaining inaccuracies in model predictions can be attributed to the limits of the modelling approach with regard to mechanisms, such as modulation masking and informational masking.

Original languageEnglish
Pages (from-to)2849-2859
Number of pages11
JournalJournal of the Acoustical Society of America
Volume155
Issue number4
DOIs
Publication statusPublished - 1 Apr 2024

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