Huckvale, Mark; Hilkhuysen, Gaston; (2024) Evaluating a 3-factor listener model for prediction of speech intelligibility to hearing-impaired listeners. In: Interspeech 2025. (pp. pp. 872-876). ISCA: Kos, Greece.

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Abstract

A speech intelligibility prediction model for hearing impaired listeners would be useful in the development of better signal enhancement methods and for the fitting of hearing aids. Most current prediction models use only information from a pure-tone audiogram to characterise impaired listeners, although evidence suggests that listeners vary in ways not captured by pure-tone thresholds. In this paper we evaluate a model in which each listener is described by three factors: average pure-tone thresholds, sensitivity to phonetic distortion and sensitivity to word likelihood. We build and evaluate the model using the corpus collected by the second Clarity Prediction Challenge, which contains over 13,000 intelligibility judgments by 31 hearing impaired listeners. We describe how the factors were estimated and test their independence. We show that incorporating the listener-dependent factors into an existing intelligibility metric can improve the accuracy of prediction on held-out test data with a 9.8% relative improvement in prediction error.

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