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    An acoustically-driven vocal tract model for stop consonant production

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    StoryBunton_VocalTractModel_Sp ...
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    Author
    Story, Brad H. cc
    Bunton, Kate
    Affiliation
    Univ Arizona, Speech Acoust Lab, Dept Speech Language & Hearing Sci
    Issue Date
    2017-03
    Keywords
    Vocal tract
    Speech modeling
    Area function
    Formant
    Resonance
    Speech synthesis
    
    Metadata
    Show full item record
    Publisher
    ELSEVIER SCIENCE BV
    Citation
    An acoustically-driven vocal tract model for stop consonant production 2017, 87:1 Speech Communication
    Journal
    Speech Communication
    Rights
    © 2016 Elsevier B.V. All rights reserved.
    Collection Information
    This item from the UA Faculty Publications collection is made available by the University of Arizona with support from the University of Arizona Libraries. If you have questions, please contact us at repository@u.library.arizona.edu.
    Abstract
    The purpose of this study was to further develop a multi-tier model of the vocal tract area function in which the modulations of shape to produce speech are generated by the product of a vowel substrate and a consonant superposition function. The new approach consists of specifying input parameters for a target consonant as a set of directional changes in the resonance frequencies of the vowel substrate. Using calculations of acoustic sensitivity functions, these "resonance deflection patterns" are transformed into time-varying deformations of the vocal tract shape without any direct specification of location or extent of the consonant constriction along the vocal tract. The configuration of the constrictions and expansions that are generated by this process were shown to be physiologically-realistic and produce speech sounds that are easily identifiable as the target consonants. This model is a useful enhancement for area function-based synthesis and can serve as a tool for understanding how the vocal tract is shaped by a talker during speech production. (C) 2016 Elsevier B.V. All rights reserved.
    Note
    24 month embargo; Available online 9 December 2016
    ISSN
    01676393
    PubMed ID
    28093574
    DOI
    10.1016/j.specom.2016.12.001
    Version
    Final accepted manuscript
    Sponsors
    NIH [R01-DC011275]; NSF [BCS-1145011]
    Additional Links
    http://linkinghub.elsevier.com/retrieve/pii/S0167639316301996
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.specom.2016.12.001
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    UA Faculty Publications

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