Literature DB >> 6707316

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

B Delgutte, N Y Kiang.   

Abstract

Discharge patterns of auditory-nerve fibers in anesthetized cats were recorded in response to a set of nine steady-state, two-formant vowels presented at 60 and 75 dB SPL. The largest components in the discrete Fourier transforms of period histograms were almost always harmonics of the vowel fundamental frequency that were close to one of the formant frequencies, the fundamental frequency or the fiber characteristic frequency (CF). For any fiber, the position of its CF relative to the formant frequencies (F1 and F2) appears to determine which of these components dominates the response. Specifically, the response characteristics of the tonotopically arranged array of fibers can be described in terms of five CF regions: (1) a low-CF region below F1 in which the largest response components are the harmonics of the fundamental frequency closest to CF; (2) a region centered around CF = F1 in which the first formant and its harmonics are the largest components; (3) an intermediate region between F1 and F2 with prominent components at both the fiber CF and the fundamental frequency; (4) a region centered around CF = F2 in which harmonics close to the second formant are the largest for frequencies above the fundamental; and (5) a high-CF region in which response spectra tend to show broad, multiple peaks at the formant and fundamental frequencies. These CF regions are related to the phonetic descriptions of vowels. For example, the extent of the low-CF region is largest for "open" vowels (which have a high F1), and the intermediate region is distinct only for "spread" vowels for which F1 and F2 are more than 1.5-2 octaves apart. For all vowels, response activity for the majority of fibers is concentrated near the formant frequencies, in contrast to responses to broadband noise for which components near CF are dominant.

Entities:  

Mesh:

Year:  1984        PMID: 6707316     DOI: 10.1121/1.390596

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


  39 in total

1.  Improved neural representation of vowels in electric stimulation using desynchronizing pulse trains.

Authors:  Leonid Litvak; Bertrand Delgutte; Donald Eddington
Journal:  J Acoust Soc Am       Date:  2003-10       Impact factor: 1.840

2.  Different timescales for the neural coding of consonant and vowel sounds.

Authors:  Claudia A Perez; Crystal T Engineer; Vikram Jakkamsetti; Ryan S Carraway; Matthew S Perry; Michael P Kilgard
Journal:  Cereb Cortex       Date:  2012-03-16       Impact factor: 5.357

3.  Speech enhancement for listeners with hearing loss based on a model for vowel coding in the auditory midbrain.

Authors:  Akshay Rao; Laurel H Carney
Journal:  IEEE Trans Biomed Eng       Date:  2014-03-25       Impact factor: 4.538

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

Authors:  Qing Tan; Laurel H Carney
Journal:  J Acoust Soc Am       Date:  2006-09       Impact factor: 1.840

5.  Spectral integration plasticity in cat auditory cortex induced by perceptual training.

Authors:  M Diane Keeling; Barbara M Calhoun; Katharina Krüger; Daniel B Polley; Christoph E Schreiner
Journal:  Exp Brain Res       Date:  2007-09-21       Impact factor: 1.972

6.  Acoustic and auditory phonetics: the adaptive design of speech sound systems.

Authors:  Randy L Diehl
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-03-12       Impact factor: 6.237

7.  Neural representation of spectral and temporal information in speech.

Authors:  Eric D Young
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2008-03-12       Impact factor: 6.237

8.  The role of broadband inhibition in the rate representation of spectral cues for sound localization in the inferior colliculus.

Authors:  Bradford J May; Michael Anderson; Matthew Roos
Journal:  Hear Res       Date:  2008-01-26       Impact factor: 3.208

9.  Independent population coding of speech with sub-millisecond precision.

Authors:  Jose A Garcia-Lazaro; Lucile A C Belliveau; Nicholas A Lesica
Journal:  J Neurosci       Date:  2013-12-04       Impact factor: 6.167

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

Authors:  Björn Lindblom; Randy Diehl; Carl Creeger
Journal:  Speech Commun       Date:  2009-07-01       Impact factor: 2.017

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