Literature DB >> 29092534

Formant-frequency discrimination of synthesized vowels in budgerigars (Melopsittacus undulatus) and humans.

Kenneth S Henry1, Kassidy N Amburgey2, Kristina S Abrams3, Fabio Idrobo4, Laurel H Carney5.   

Abstract

Vowels are complex sounds with four to five spectral peaks known as formants. The frequencies of the two lowest formants, F1and F2, are sufficient for vowel discrimination. Behavioral studies show that many birds and mammals can discriminate vowels. However, few studies have quantified thresholds for formant-frequency discrimination. The present study examined formant-frequency discrimination in budgerigars (Melopsittacus undulatus) and humans using stimuli with one or two formants and a constant fundamental frequency of 200 Hz. Stimuli had spectral envelopes similar to natural speech and were presented with random level variation. Thresholds were estimated for frequency discrimination of F1, F2, and simultaneous F1 and F2 changes. The same two-down, one-up tracking procedure and single-interval, two-alternative task were used for both species. Formant-frequency discrimination thresholds were as sensitive in budgerigars as in humans and followed the same patterns across all conditions. Thresholds expressed as percent frequency difference were higher for F1 than for F2, and were unchanged between stimuli with one or two formants. Thresholds for simultaneous F1 and F2 changes indicated that discrimination was based on combined information from both formant regions. Results were consistent with previous human studies and show that budgerigars provide an exceptionally sensitive animal model of vowel feature discrimination.

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Year:  2017        PMID: 29092534      PMCID: PMC5640449          DOI: 10.1121/1.5006912

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


  39 in total

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Authors:  J Lyzenga; J W Horst
Journal:  J Acoust Soc Am       Date:  1998-11       Impact factor: 1.840

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Journal:  J Neurophysiol       Date:  1988-12       Impact factor: 2.714

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

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Authors:  R D Hienz; C M Aleszczyk; B J May
Journal:  J Acoust Soc Am       Date:  1996-08       Impact factor: 1.840

9.  Perceptual organization of acoustic stimuli by budgerigars (Melopsittacus undulatus): I. Pure tones.

Authors:  Robert J Dooling; Susan D Brown; Thomas J Park; Kazuo Okanoya; Sigfrid D Soli
Journal:  J Comp Psychol       Date:  1987-06       Impact factor: 2.231

10.  Conserved mechanisms of vocalization coding in mammalian and songbird auditory midbrain.

Authors:  Sarah M N Woolley; Christine V Portfors
Journal:  Hear Res       Date:  2013-05-31       Impact factor: 3.208

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  6 in total

Review 1.  Animal models of hidden hearing loss: Does auditory-nerve-fiber loss cause real-world listening difficulties?

Authors:  Kenneth S Henry
Journal:  Mol Cell Neurosci       Date:  2021-12-07       Impact factor: 4.314

2.  Effects of selective auditory-nerve damage on the behavioral audiogram and temporal integration in the budgerigar.

Authors:  Stephanie J Wong; Kristina S Abrams; Kassidy N Amburgey; Yingxuan Wang; Kenneth S Henry
Journal:  Hear Res       Date:  2019-01-23       Impact factor: 3.208

3.  Normal Tone-In-Noise Sensitivity in Trained Budgerigars despite Substantial Auditory-Nerve Injury: No Evidence of Hidden Hearing Loss.

Authors:  Kenneth S Henry; Kristina S Abrams
Journal:  J Neurosci       Date:  2020-11-11       Impact factor: 6.167

4.  Identifying cues for tone-in-noise detection using decision variable correlation in the budgerigar (Melopsittacus undulatus).

Authors:  Kenneth S Henry; Kassidy N Amburgey; Kristina S Abrams; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2020-02       Impact factor: 1.840

5.  Effects of Kainic Acid-Induced Auditory Nerve Damage on Envelope-Following Responses in the Budgerigar (Melopsittacus undulatus).

Authors:  John L Wilson; Kristina S Abrams; Kenneth S Henry
Journal:  J Assoc Res Otolaryngol       Date:  2020-10-19

6.  Midbrain-Level Neural Correlates of Behavioral Tone-in-Noise Detection: Dependence on Energy and Envelope Cues.

Authors:  Yingxuan Wang; Kristina S Abrams; Laurel H Carney; Kenneth S Henry
Journal:  J Neurosci       Date:  2021-07-15       Impact factor: 6.167

  6 in total

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