Bayesian estimation of high-parameter models of the auditory filter

Abstract

The Bayesian adaptive procedure proposed by Shen and Richards [J. Acoust. Soc. Am. 134(2), 1134–1145 (2013)] was extended to allow the rapid estimation of auditory filters that were asymmetric about their peak frequencies. The estimation of the auditory-filter shape (five free parameters) was achieved using single Bayesian adaptive tracks of 150–200 trials (approximately 15 min to complete). During the experimental track, listeners detected a tonal signal presented with either simultaneous or forward maskers. Both types of maskers consisted of two bands of noises, one on each side of the signal frequency. The Bayesian adaptive procedure iteratively updated the parameter estimates following each experimental trial and determined the stimulus that would maximize the gain of information on the following trial. The stimuli were adaptively manipulated along three dimensions: the masker level and the spectral location of the upper and lower masker bands. The proposed procedure allowed the reliable estimation of the auditory-filter shape for naïve normal-hearing listeners. The model predictions replicated the known effect of the masker-signal simultaneity on the auditory filter.