Psychometric functions for informational masking.

J Acoust Soc Am

Waisman Center, University of Wisconsin, Madison, Wisconsin 53705, USA.

Published: December 2003

The term informational masking has traditionally been used to refer to elevations in signal threshold resulting from masker uncertainty. In the present study, the method of constant stimuli was used to obtain complete psychometric functions (PFs) from 44 normal-hearing listeners in conditions known to produce varying amounts of informational masking. The listener's task was to detect a pure-tone signal in the presence of a broadband noise masker (low masker uncertainty) and in the presence of multitone maskers with frequencies and amplitudes that varied at random from one presentation to the next (high masker uncertainty). Relative to the broadband noise condition, significant reductions were observed in both the slope and the upper asymptote of the PF for multitone maskers producing large amounts of informational masking. Slope was affected more for some listeners and conditions while asymptote was affected more for others; consequently, neither parameter alone was highly predictive of individual thresholds or the amount of informational masking. Mean slopes and asymptotes varied nonmonotonically with the number of masker components in a manner similar to mean thresholds, particularly when the estimated effect of energetic masking on thresholds was subtracted out. As in past studies, the threshold data were well described by a model in which trial-by-trial judgments are based on a weighted sum of levels in dB at the output of independent auditory filters. The psychometric data, however, complicated the model's interpretation in two ways: First, they suggested that, depending on the listener and condition, the weights can either reflect a fixed influence of masker components on each trial or the effect of occasionally mistaking a masker component for the signal from trial to trial. Second, they indicated that in either case the variance of the underlying decision variable as estimated from PF slope is not by itself great enough to account for the observed changes in informational masking.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC2858973PMC
http://dx.doi.org/10.1121/1.1629303DOI Listing

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