Literature DB >> 17004467

Predictions of formant-frequency discrimination in noise based on model auditory-nerve responses.

Qing Tan1, Laurel H Carney.   

Abstract

To better understand how the auditory system extracts speech signals in the presence of noise, discrimination thresholds for the second formant frequency were predicted with simulations of auditory-nerve responses. These predictions employed either average-rate information or combined rate and timing information, and either populations of model fibers tuned across a wide range of frequencies or a subset of fibers tuned to a restricted frequency range. In general, combined temporal and rate information for a small population of model fibers tuned near the formant frequency was most successful in replicating the trends reported in behavioral data for formant-frequency discrimination. To explore the nature of the temporal information that contributed to these results, predictions based on model auditory-nerve responses were compared to predictions based on the average rates of a population of cross-frequency coincidence detectors. These comparisons suggested that average response rate (count) of cross-frequency coincidence detectors did not effectively extract important temporal information from the auditory-nerve population response. Thus, the relative timing of action potentials across auditory-nerve fibers tuned to different frequencies was not the aspect of the temporal information that produced the trends in formant-frequency discrimination thresholds.

Mesh:

Year:  2006        PMID: 17004467      PMCID: PMC2572872          DOI: 10.1121/1.2225858

Source DB:  PubMed          Journal:  J Acoust Soc Am        ISSN: 0001-4966            Impact factor:   1.840


  31 in total

1.  Vowel discrimination in cats: acquisition, effects of stimulus level, and performance in noise.

Authors:  R D Hienz; C M Aleszczyk; B J May
Journal:  J Acoust Soc Am       Date:  1996-06       Impact factor: 1.840

2.  Responses to amplitude-modulated tones in the auditory nerve of the cat.

Authors:  P X Joris; T C Yin
Journal:  J Acoust Soc Am       Date:  1992-01       Impact factor: 1.840

3.  Fundamental frequency effects on thresholds for vowel formant discrimination.

Authors:  D Kewley-Port; X Li; Y Zheng; A T Neel
Journal:  J Acoust Soc Am       Date:  1996-10       Impact factor: 1.840

4.  Strategies for the representation of a tone in background noise in the temporal aspects of the discharge patterns of auditory-nerve fibers.

Authors:  M I Miller; P E Barta; M B Sachs
Journal:  J Acoust Soc Am       Date:  1987-03       Impact factor: 1.840

5.  Frequency map of the spiral ganglion in the cat.

Authors:  E M Keithley; R C Schreiber
Journal:  J Acoust Soc Am       Date:  1987-04       Impact factor: 1.840

6.  Rate responses of auditory nerve fibers to tones in noise near masked threshold.

Authors:  E D Young; P E Barta
Journal:  J Acoust Soc Am       Date:  1986-02       Impact factor: 1.840

7.  Speech coding in the auditory nerve: V. Vowels in background noise.

Authors:  B Delgutte; N Y Kiang
Journal:  J Acoust Soc Am       Date:  1984-03       Impact factor: 1.840

8.  Speech coding in the auditory nerve: I. Vowel-like sounds.

Authors:  B Delgutte; N Y Kiang
Journal:  J Acoust Soc Am       Date:  1984-03       Impact factor: 1.840

9.  Formant-frequency discrimination for isolated English vowels.

Authors:  D Kewley-Port; C S Watson
Journal:  J Acoust Soc Am       Date:  1994-01       Impact factor: 1.840

10.  Difference limens for formant patterns of vowel sounds.

Authors:  J W Hawks
Journal:  J Acoust Soc Am       Date:  1994-02       Impact factor: 1.840

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  2 in total

1.  Neural-scaled entropy predicts the effects of nonlinear frequency compression on speech perception.

Authors:  Varsha H Rallapalli; Joshua M Alexander
Journal:  J Acoust Soc Am       Date:  2015-11       Impact factor: 1.840

2.  Human discrimination and modeling of high-frequency complex tones shed light on the neural codes for pitch.

Authors:  Daniel R Guest; Andrew J Oxenham
Journal:  PLoS Comput Biol       Date:  2022-03-03       Impact factor: 4.475

  2 in total

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