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A Two-interval Forced-choice Task for Multisensory Comparisons
07:13

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Psychometric functions for pure-tone frequency discrimination.

Huanping Dai1, Christophe Micheyl

  • 1Department of Speech, Language, and Hearing Sciences, University of Arizona, 1131 East 2nd Street, Tucson, Arizona, 85721, USA. hdai@email.arizona.edu

The Journal of the Acoustical Society of America
|July 27, 2011
PubMed
Summary
This summary is machine-generated.

Auditory frequency discrimination models should assume a linear relationship between sensitivity (d') and frequency difference (Δf). Accounting for attentional lapses reveals this linear link across various sound frequencies and levels.

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Area of Science:

  • Auditory perception
  • Psychoacoustics
  • Signal detection theory

Background:

  • The psychometric function (PF) describes auditory perception thresholds.
  • Understanding the form of the PF for frequency discrimination is crucial for auditory models.

Purpose of the Study:

  • To investigate the relationship between sensitivity (d") and frequency difference (Δf) in pure-tone frequency discrimination.
  • To assess the impact of attentional lapses on estimating the slope of the psychometric function.

Main Methods:

  • Measured PFs for pure-tone frequency discrimination across various frequencies (200-8000 Hz) and sound pressure levels (SPLs).
  • Fitted proportion-correct data using a cumulative-Gaussian function of d', where d' was a power transformation of Δf.
  • Investigated the influence of attentional lapses by including lapse rate as a free parameter in the model fits.

Main Results:

  • Without accounting for lapses, PF slopes on log(d')-log(Δf) plots were significantly less than 1, suggesting non-linearity.
  • Including lapse rate in the fits resulted in PF slopes not significantly different from 1, indicating a linear d'-Δf relationship.
  • This linear relationship held across tested frequencies and SPLs.

Conclusions:

  • A linear relationship between d' and Δf is consistent with auditory frequency discrimination data when attentional lapses are considered.
  • Spectral and temporal models of auditory frequency discrimination should incorporate this linear relationship across a broad range of acoustic parameters.