Personalization of Hearing Aid Fitting Based on Adaptive Dynamic Range Optimization

Abstract

Adaptive dynamic range optimization (ADRO) is a hearing aid fitting rationale which involves adjusting the gains in a number of frequency bands by using a series of rules. The rules reflect the comparison of the estimated percentile occurrences of the sound levels with the audibility and comfort hearing levels of a person suffering from hearing loss. In the study reported in this paper, a previously developed machine learning method was utilized to personalize the ADRO fitting in order to provide an improved hearing experience as compared to the standard ADRO hearing aid fitting. The personalization was carried out based on the user preference model within the framework of maximum likelihood inverse reinforcement learning. The testing of ten subjects with hearing loss was conducted, which indicated that the personalized ADRO was preferred over the standard ADRO on average by about 10 times. Furthermore, a word recognition experiment was conducted, which showed that the personalized ADRO had no adverse impact on speech understanding as compared to the standard ADRO.

A Review of Machine Learning Approaches for the Personalization of Amplification in Hearing Aids

“…In [ 34 ], a study on Adaptive Dynamic Range Optimization (ADRO), it was demonstrated that the training could be conducted in an adaptive manner via the MLIRL method based on the incoming sound-level percentiles and a user’s hearing comfort level. The experimental setup involved ten participants with mild to moderately severe hearing loss.…”

Bioinspired Artificial Intelligence Applications 2023

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