Thoughts on the potential to compensate a hearing loss in noise

TL;DR

This paper explores a novel approach to mitigate the effects of signal distortion in hearing-impaired individuals in noisy environments by using a dynamic range manipulation scheme based on an ASR model, potentially improving speech recognition.

Contribution

It introduces a patented spectral modulation expansion method (PLATT) to compensate for class D hearing loss effects caused by level uncertainty, enhancing speech perception in noise.

Findings

More than half of class D loss may be compensable.

Spectral modulation expansion improves speech recognition thresholds.

ASR-based evaluation supports the method's effectiveness.

Abstract

The effect of hearing impairment on speech perception was described by Plomp (1978) as a sum of a loss of class A, due to signal attenuation, and a loss of class D, due to signal distortion. While a loss of class A can be compensated by linear amplification, a loss of class D, which severely limits the benefit of hearing aids in noisy listening conditions, cannot. Not few users of hearing aids keep complaining about the limited benefit of their devices in noisy environments. Recently, in an approach to model human speech recognition by means of a re-purposed automatic speech recognition system, the loss of class D was explained by introducing a level uncertainty which reduces the individual accuracy of spectro-temporal signal levels. Based on this finding, an implementation of a patented dynamic range manipulation scheme (PLATT) is proposed, which aims to mitigate the effect of increased level uncertainty on speech recognition in noise by expanding spectral modulation patterns in the range of 2 to 4 ERB. An objective evaluation of the benefit in speech recognition thresholds in noise using an ASR-based speech recognition model suggests that more than half of the class D loss due to an increased level uncertainty might be compensable.