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Robust and efficient Bayesian adaptive psychometric function estimation

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Title: Robust and efficient Bayesian adaptive psychometric function estimation
Authors: Doire, CSJ
Brookes, DM
Naylor, PA
Item Type: Journal Article
Abstract: The efficient measurement of the threshold and slope of the psychometric function (PF) is an important objective in psychoacoustics. This paper proposes a procedure that combines a Bayesian estimate of the PF with either a look one-ahead or a look two-ahead method of selecting the next stimulus presentation. The procedure differs from previously proposed algorithms in two respects: (i) it does not require the range of possible PF parameters to be specified in advance and (ii) the sequence of probe signal-to-noise ratios optimizes the threshold and slope estimates at a performance level, ϕ, that can be chosen by the experimenter. Simulation results show that the proposed procedure is robust and that the estimates of both threshold and slope have a consistently low bias. Over a wide range of listener PF parameters, the root-mean-square errors after 50 trials were ∼1.2 dB in threshold and 0.14 in log-slope. It was found that the performance differences between the look one-ahead and look two-ahead methods were negligible and that an entropy-based criterion for selecting the next stimulus was preferred to a variance-based criterion.
Issue Date: 10-Apr-2017
Date of Acceptance: 20-Mar-2017
URI: http://hdl.handle.net/10044/1/45766
DOI: https://dx.doi.org/10.1121/1.4979580
ISSN: 0001-4966
Publisher: Acoustical Society of America
Start Page: 2501
End Page: 2512
Journal / Book Title: Journal of the Acoustical Society of America
Volume: 141
Issue: 4
Copyright Statement: © 2017 Author(s). All article content, except where otherwise noted, is licensed under a Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/) .
Sponsor/Funder: Commission of the European Communities
Engineering & Physical Science Research Council (EPSRC)
Funder's Grant Number: PITN-GA-2012-316969
Keywords: Acoustics
MD Multidisciplinary
Publication Status: Published
Appears in Collections:Electrical and Electronic Engineering
Faculty of Engineering