An Evolutionary Multi-objective Optimization Approach to Design the Sound Processor of a Hearing Aid

Abstract

Hearing impairment is one of the most common problems nowadays which affects the quality of life in terms of speech understanding and communication abilities. Therefore, untreated hearing loss may negatively impact social life. Mild to moderate hearing loss may be compensated by employing a hearing aid. The hearing aid performs sub-band division of the auditory signal, and then amplifies each sub-band in order to correct the patient’s audiogram. Designing the hearing aid sound processor for optimal audiogram correction requires the determination of the number of sub-bands, filter order and sub-band gains respectively. Considering the conflicting nature between solution quality and hardware resources, designing the sound processor is a matter of compromise. This article proposes an evolutionary approach to designing the sound processor, which treats the design as a multi-objective optimization (MOO) problem. Thus, the sub-band number, the sub-band filter order and the audiogram correction function are simultaneously optimized. The determination of the subband gains, for a given configuration of sub-band number and filter order, is treated as a single-objective optimization (SOO) problem. Dedicated genetic algorithms (GA) are used to solve both MOO and SOO problems. The MOO was handled with the Pareto frontier method. The functionality of the proposed design algorithm is illustrated on two conclusive design examples for optimal audiogram correction.