Genetic Algorithms for Adaptive Psychophysical Procedures: Recipient-Directed Design of Speech-Processor MAPs

Abstract

The goal of the research is to evaluate the application of genetic algorithms (GAs) in listener-directed optimization of audio-processing designs. We hypothesize that cochlear-implant recipients can use a GA-guided adaptive psychophysical search procedure to select useful designs from among a large number of speech processor MAPS. An adaptive psychophysical procedure was developed in which a listener's preferred four out of eight speech processor MAPs were updated according to a genetic algorithm. Experiments involving cochlear-implant recipients were conducted to characterize both the convergence behavior of the adaptive procedure as well as properties of the MAPs optimized by the recipient. Results from five cochlear-implant recipients indicate that the adaptive procedure converges to useful speech processor MAPs within twenty iterations. The results suggest a means whereby a potentially large number of audio-processing designs can be searched efficiently by a human listener without requiring excessive amounts of feedback or prior knowledge about the listener's preferences. In the case of cochlear-implant recipients, it may be possible to use this procedure as an aid to the clinician in the fitting of a speech processor MAP.