Application of auditory models to assessing the sound quality of hearing aid signal processing algorithms.

Abstract

Advances in systems technology allow for increasingly complex processing algorithms in hearing systems addressing increasingly complex acoustic conditions. These developments have the potential of improving the rehabilitation of hearing impairment, but establishing reliable measures of benefit is quite difficult for these complex algorithms and conditions. Being the “gold standard” for algorithm evaluation, subjective testing of hearing-impaired subjects has some limitations in this context. It is very time consuming and the long acclimatization time needed when listening with new devices in complex acoustic conditions cannot easily be accounted for. Therefore, objective methods for estimating the benefit of an algorithm in a certain acoustic condition are desirable. They allow for identifying promising candidate algorithms and the acoustic conditions in which the algorithms might be applicable and thus identify critical acoustic conditions to be tested subjectively. In addition and in combination with technical measures such as segmental signal-to-noise ratio and distortion measures, perceptual measures based on auditory models might be useful for developing meaningful objective measures. This talk presents recent applications of auditory models to objective algorithm evaluation. Because of the growing importance of binaural and multi-microphone processing in hearing instruments, binaural/multichannel models for speech intelligibility and quality will be emphasized.