Inference of the distortion component of hearing impairment from speech recognition by predicting the effect of the attenuation component

Abstract

Objective

A model-based determination of the average supra-threshold (“distortion”) component of hearing impairment which limits the benefit of hearing aid amplification.

Design

Published speech recognition thresholds (SRTs) were predicted with the framework for auditory discrimination experiments (FADE), which simulates recognition processes, the speech intelligibility index (SII), which exploits frequency-dependent signal-to-noise ratios (SNR), and a modified SII with a hearing-loss-dependent band importance function (PAV). Their attenuation-component-based prediction errors were interpreted as estimates of the distortion component.

Study sample

Unaided SRTs of 315 hearing-impaired ears measured with the German matrix sentence test in stationary noise.

Results

Overall, the models showed root-mean-square errors (RMSEs) of 7 dB, but for steeply sloping hearing loss FADE and PAV were more accurate (RMSE = 9 dB) than the SII (RMSE = 23 dB). Prediction errors of FADE and PAV increased linearly with the average hearing loss. The consideration of the distortion component estimate significantly improved the accuracy of FADE’s and PAV’s predictions.

Conclusions

The supra-threshold distortion component—estimated by prediction errors of FADE and PAV—seems to increase with the average hearing loss. Accounting for a distortion component improves the model predictions and implies a need for effective compensation strategies for supra-threshold processing deficits with increasing audibility loss.

Keywords:

• Speech intelligibility modelling
• FADE
• SII
• hearing impairment
• estimation of supra-threshold hearing loss

Correction Statement

This article has been republished with minor changes. These changes do not impact the academic content of the article.

Disclosure statement

The authors declare that there is no conflict of interest.

Notes

1 Reference implementation: www.sii.to.

2 Reference implementation: https://github.com/m-r-s/fade.

Additional information

Funding

This work was supported by the Cluster of Excellence Grant “Hearing4all” (DFG Project Number 390895286).