A Probabilistic Modeling Approach to Hearing Loss Compensation
Abstract
Hearing Aid (HA) algorithms need to be tuned ("fitted") to match the impairment of each specific patient. The lack of a fundamental HA fitting theory is a strong contributing factor to an unsatisfying sound experience for about 20% of hearing aid patients. This paper proposes a probabilistic modeling approach to the design of HA algorithms. The proposed method relies on a generative probabilistic model for the hearing loss problem and provides for automated inference of the corresponding (1) signal processing algorithm, (2) the fitting solution as well as a principled (3) performance evaluation metric. All three tasks are realized as message passing algorithms in a factor graph representation of the generative model, which in principle allows for fast implementation on hearing aid or mobile device hardware. The methods are theoretically worked out and simulated with a custom-built factor graph toolbox for a specific hearing loss model.
Cite
@article{arxiv.1602.01345,
title = {A Probabilistic Modeling Approach to Hearing Loss Compensation},
author = {Thijs van de Laar and Bert de Vries},
journal= {arXiv preprint arXiv:1602.01345},
year = {2016}
}