Literature DB >> 6707317

Speech coding in the auditory nerve: II. Processing schemes for vowel-like sounds.

B Delgutte.   

Abstract

Several processing schemes by which phonetically important information for vowels can be extracted from responses of auditory-nerve fibers are analyzed. The schemes are based on power spectra of period histograms obtained in response to a set of nine two-formant, steady-state, vowel-like stimuli presented at 60 and 75 dB SPL. One class of "local filtering" schemes, which was originally proposed by Young and Sachs [J. Acoust. Soc. Am. 66, 1381-1403 (1979)], consists of analyzing response patterns by filters centered at the characteristic frequencies (CF) of the fibers, so that a tonotopically arranged measure of synchronized response can be obtained. Various schemes in this class differ in the characteristics of the filter. For a wide range of filter bandwidths, formant frequencies correspond approximately to the CFs for which the response measure is maximal. If in addition, the bandwidths of the analyzing filters are made compatible with psychophysical measures of frequency selectivity, low-frequency harmonics of the stimulus fundamental are resolved in the output profile, so that fundamental frequency can also be estimated. In a second class of processing schemes, a dominant response component is defined for each fiber from a 1/6 octave spectral representation of the response pattern, and the formant frequencies are estimated from the most frequent values of the dominant component in the ensemble of auditory-nerve fibers. The local filtering schemes and the dominant component schemes can be related to "place" and "periodicity" models of auditory processing, respectively.

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Year:  1984        PMID: 6707317     DOI: 10.1121/1.390597

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


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

Authors:  Akshay Rao; Laurel H Carney
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5.  Orderly cortical representation of vowels based on formant interaction.

Authors:  F W Ohl; H Scheich
Journal:  Proc Natl Acad Sci U S A       Date:  1997-08-19       Impact factor: 11.205

Review 6.  How We Hear: The Perception and Neural Coding of Sound.

Authors:  Andrew J Oxenham
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Journal:  J Comp Physiol A       Date:  1990-02       Impact factor: 1.836

8.  Speech discrimination after early exposure to pulsed-noise or speech.

Authors:  Kamalini G Ranasinghe; Ryan S Carraway; Michael S Borland; Nicole A Moreno; Elizabeth A Hanacik; Robert S Miller; Michael P Kilgard
Journal:  Hear Res       Date:  2012-05-02       Impact factor: 3.208

9.  Distorting temporal fine structure by phase shifting and its effects on speech intelligibility and neural phase locking.

Authors:  Yingyue Xu; Maxin Chen; Petrina LaFaire; Xiaodong Tan; Claus-Peter Richter
Journal:  Sci Rep       Date:  2017-10-17       Impact factor: 4.379

10.  Mammalian behavior and physiology converge to confirm sharper cochlear tuning in humans.

Authors:  Christian J Sumner; Toby T Wells; Christopher Bergevin; Joseph Sollini; Heather A Kreft; Alan R Palmer; Andrew J Oxenham; Christopher A Shera
Journal:  Proc Natl Acad Sci U S A       Date:  2018-10-15       Impact factor: 11.205

  10 in total

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