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Analysis of the aerodynamic sound of speech through static vocal tract models of various glottal shapes
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Mechanics. (Linné FLOW Centre)
KTH, School of Engineering Sciences (SCI), Centres, Linné Flow Center, FLOW. KTH, School of Engineering Sciences (SCI), Mechanics.ORCID iD: 0000-0001-7330-6965
2019 (English)In: Journal of Biomechanics, ISSN 0021-9290, E-ISSN 1873-2380, article id 109484Article in journal (Refereed) Published
Abstract [en]

The acoustic spectrum of our voice can be divided into harmonic and inharmonic sound components. While the harmonic components, generated by the oscillatory motion of the vocal folds, are well described by reduced-order speech models, the accurate computation of the inharmonic components requires high-order flow simulations, which predict the vortex shedding and turbulent structures present in the shear layers of the glottal jet. This study characterizes the dominant frequencies in the unsteady flow of the intra- and supraglottal region. A realistic vocal tract geometry obtained through magnetic resonance imaging (MRI) is applied for the numerical domain, which is locally modified to account for different convergent and divergent glottal angles. Both time-averaged and fluctuating values of the flow variables are computed and their distribution at various glottal shapes is compared. The impact of the registered modes in the unsteady flow on the acoustic far field is computed through direct compressible flow simulations. Furthermore, acoustic analogies are applied to localize the sources of the aerodynamically generated sound.

Place, publisher, year, edition, pages
Elsevier, 2019. article id 109484
Keywords [en]
Human Phonation, Large Eddy Simulation, Aeroacoustics, Magnetic Resonance Imaging
National Category
Fluid Mechanics and Acoustics
Research subject
Engineering Mechanics
Identifiers
URN: urn:nbn:se:kth:diva-263772DOI: 10.1016/j.jbiomech.2019.109484OAI: oai:DiVA.org:kth-263772DiVA, id: diva2:1369739
Funder
Swedish Research Council, VR 621-2012-4256
Note

QC 20191115

Available from: 2019-11-12 Created: 2019-11-12 Last updated: 2019-11-15Bibliographically approved

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