Literature DB >> 19830253

Do 'Dominant Frequencies' explain the listener's response to formant and spectrum shape variations?

Björn Lindblom1, Randy Diehl, Carl Creeger.   

Abstract

Psychoacoustic experimentation shows that formant frequency shifts can give rise to more significant changes in phonetic vowel timber than differences in overall level, bandwidth, spectral tilt, and formant amplitudes. Carlson and Granström's perceptual and computational findings suggest that, in addition to spectral representations, the human ear uses temporal information on formant periodicities ('Dominant Frequencies') in building vowel timber percepts. The availability of such temporal coding in the cat's auditory nerve fibers has been demonstrated in numerous physiological investigations undertaken during recent decades. In this paper we explore, and provide further support for, the Dominant Frequency hypothesis using KONVERT, a computational auditory model. KONVERT provides auditory excitation patterns for vowels by performing a critical-band analysis. It simulates phase locking in auditory neurons and outputs DF histograms. The modeling supports the assumption that listeners judge phonetic distance among vowels on the basis formant frequency differences as determined primarily by a time-based analysis. However, when instructed to judge psychophysical distance among vowels, they can also use spectral differences such as formant bandwidth, formant amplitudes and spectral tilt. Although there has been considerable debate among psychoacousticians about the functional role of phase locking in monaural hearing, the present research suggests that detailed temporal information may nonetheless play a significant role in speech perception.

Entities:  

Year:  2009        PMID: 19830253      PMCID: PMC2760739          DOI: 10.1016/j.specom.2008.12.003

Source DB:  PubMed          Journal:  Speech Commun        ISSN: 0167-6393            Impact factor:   2.017


  5 in total

1.  Modeling the perception of concurrent vowels: vowels with the same fundamental frequency.

Authors:  P F Assmann; Q Summerfield
Journal:  J Acoust Soc Am       Date:  1989-01       Impact factor: 1.840

2.  Phase-locked response to low-frequency tones in single auditory nerve fibers of the squirrel monkey.

Authors:  J E Rose; J F Brugge; D J Anderson; J E Hind
Journal:  J Neurophysiol       Date:  1967-07       Impact factor: 2.714

3.  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

4.  Suggested formulae for calculating auditory-filter bandwidths and excitation patterns.

Authors:  B C Moore; B R Glasberg
Journal:  J Acoust Soc Am       Date:  1983-09       Impact factor: 1.840

5.  Modeling the judgment of vowel quality differences.

Authors:  R A Bladon; B Lindblom
Journal:  J Acoust Soc Am       Date:  1981-05       Impact factor: 1.840

  5 in total
  1 in total

1.  Speech Coding in the Brain: Representation of Vowel Formants by Midbrain Neurons Tuned to Sound Fluctuations

Authors:  Laurel H Carney; Tianhao Li; Joyce M McDonough
Journal:  eNeuro       Date:  2015-07-20
  1 in total

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