Open Access
Review
Issue
Acta Acust.
Volume 7, 2023
Article Number 25
Number of page(s) 18
Section Speech
DOI https://doi.org/10.1051/aacus/2023014
Published online 02 June 2023
  1. F. Alipour, C. Brucker, D. Cook, A. Gommel, M. Kaltenbacher, W. Mattheus, L. Mongeau, E. Nauman, R. Schwarze, I. Tokuda, S. Zorner: Mathematical models and numerical schemes for the simulation of human phonation, Current Bioinformatics 6, 3 (2011) 323–343. [CrossRef] [Google Scholar]
  2. Z. Zhang: Mechanics of human voice production and control. Journal of the Acoustical Society of America 140, 4 (2016) 2614–2635. [CrossRef] [PubMed] [Google Scholar]
  3. C. Calvache, L. Solaque, A. Velasco, L. Penuela: Biomechanical models to represent vocal physiology: a systematic review. Journal of Voice 37 (2023) 465.e1–465.e18. [CrossRef] [PubMed] [Google Scholar]
  4. M. Döllinger, S. Kniesburges, M. Kaltenbacher, M. Echternach: Current methods for modelling voice production. HNO 64, 2 (2016) 82–90. [CrossRef] [PubMed] [Google Scholar]
  5. A.K. Miri: Mechanical characterization of vocal fold tissue: a review study. Journal of Voice 28, 6 (2014) 657–667. [CrossRef] [PubMed] [Google Scholar]
  6. T.E. Shurtz, S.L. Thomson: Influence of numerical model decisions on the flow-induced vibration of a computational vocal fold model. Computers & Structures 122 (2013) 44–54. Computational Fluid and Solid Mechanics 2013. [CrossRef] [PubMed] [Google Scholar]
  7. M. Feistauer, J. Hasnedlová-Prokopová, J. Horáček, A. Kosík, V. Kučera: DGFEM for dynamical systems describing interaction of compressible fluid and structures. Journal of Computational and Applied Mathematics 254 (2013) 17–30. [CrossRef] [Google Scholar]
  8. J. Yang, X. Wang, M. Krane, L.T. Zhang: Fully-coupled aeroelastic simulation with fluid compressibility – For application to vocal fold vibration. Computer Methods in Applied Mechanics and Engineering 315 (2017) 584–606. [CrossRef] [PubMed] [Google Scholar]
  9. L. Schickhofer, J. Malinen, M. Mihaescu: Compressible flow simulations of voiced speech using rigid vocal tract geometries acquired by MRI. Journal of the Acoustical Society of America 145, 4 (2019) 2049–2061. [CrossRef] [PubMed] [Google Scholar]
  10. L. Schickhofer, M. Mihaescu: Analysis of the aerodynamic sound of speech through static vocal tract models of various glottal shapes. Journal of Biomechanics 99 (2020) 109484. [CrossRef] [PubMed] [Google Scholar]
  11. C.F. de Luzan, J. Chen, M. Mihaescu, S.M. Khosla, E. Gutmark: Computational study of false vocal folds effects on unsteady airflows through static models of the human larynx. Journal of Biomechanics 48, 7 (2015) 1248–1257. [CrossRef] [PubMed] [Google Scholar]
  12. P. Hájek, P. Švancara, J. Horáček, J.G. Švec: Finite-element modeling of vocal fold self-oscillations in interaction with vocal tract: Comparison of incompressible and compressible flow model. Journal of Applied and Computational Mechanics 15, 12 (2021) 133–152. [Google Scholar]
  13. R.C. Scherer, D. Shinwari, K.J. De Witt, C. Zhang, B.R. Kucinschi, A.A. Afjeh: Intraglottal pressure profiles for a symmetric and oblique glottis with a divergence angle of 10 degrees. Journal of the Acoustical Society of America 109, 4 (2001) 1616–1630. [CrossRef] [PubMed] [Google Scholar]
  14. R.C. Scherer, S. Torkaman, B.R. Kucinschi, A.A. Afjeh: Intraglottal pressures in a three-dimensional model with a non-rectangular glottal shape. Journal of the Acoustical Society of America 128, 2 (2010) 828–838. [CrossRef] [PubMed] [Google Scholar]
  15. S. Li, R.C. Scherer, M. Wan, S. Wang: The effect of entrance radii on intraglottal pressure distributions in the divergent glottis. Journal of the Acoustical Society of America 131, 2 (2012) 1371–1377. [CrossRef] [PubMed] [Google Scholar]
  16. S. Li, R.C. Scherer, L.P. Fulcher, X. Wang, L. Qiu, M. Wan, S. Wang: Effects of vertical glottal Duct Length on intraglottal pressures and phonation threshold pressure in the uniform glottis. Journal of Voice 32, 1 (2018) 8–22. [CrossRef] [PubMed] [Google Scholar]
  17. S. Li, R.C. Scherer, M. Wan, S. Wang, B. Song: Intraglottal pressure: a comparison between male and female larynxes. Journal of Voice 34, 6 (2020) 813–822. [CrossRef] [PubMed] [Google Scholar]
  18. X. Zhang, Y. Wang, W. Zhao, W. Wei, Z. Tao, H. Zhao: Vocal cord abnormal voice flow field study by modeling a bionic vocal system. Advanced Robotics 34, 1 (2020) 28–36. [CrossRef] [Google Scholar]
  19. S. Li, R.C. Scherer, M. Wan: Effects of vertical glottal duct length on intraglottal pressures in the convergent glottis. Applied Sciences 11, 10 (2021) 4535. [CrossRef] [Google Scholar]
  20. C.F. de Luzan, L. Oren, E. Gutmark, S.M. Khosla: Quantification of the intraglottal pressure induced by flow separation vortices using large eddy simulation. Journal of Voice 35, 6 (2021) 822–831. [CrossRef] [PubMed] [Google Scholar]
  21. X. Zheng, R. Mittal, S. Bielamowicz: A computational study of asymmetric glottal jet deflection during phonation. Journal of the Acoustical Society of America 129, 4 (2011) 2133–2143. [CrossRef] [PubMed] [Google Scholar]
  22. P. Šidlof, J. Horáček, V. Řidký: Parallel CFD simulation of flow in a 3D model of vibrating human vocal folds. Computers & Fluids 80 (2013) 290–300. [CrossRef] [Google Scholar]
  23. P. Šidlof, S. Zörner, A. Hüppe: A hybrid approach to the computational aeroacoustics of human voice production. Biomechanics and Modeling in Mechanobiology 14 (2015) 473–488. [CrossRef] [PubMed] [Google Scholar]
  24. S. Zörner, P. Šidlof, A. Hüppe, M. Kaltenbacher: Flow and acoustic effects in the larynx for varying geometries. Acta Acustica united with Acustica 102, 2 (2016) 257–267. [CrossRef] [Google Scholar]
  25. H. Sadeghi, S. Kniesburges, M. Kaltenbacher, A. Schützenberger, M. Döllinger: Computational models of laryngeal aerodynamics: potentials and numerical costs. Journal of Voice 33, 4 (2019) 385–400. [CrossRef] [PubMed] [Google Scholar]
  26. H. Sadeghi, S. Kniesburges, S. Falk, M. Kaltenbacher, A. Schützenberger, M. Döllinger: Towards a clinically applicable computational larynx model. Applied Sciences 9, 11 (2019) 2288. [CrossRef] [Google Scholar]
  27. H. Sadeghi, M. Döllinger, M. Kaltenbacher, S. Kniesburges: Aerodynamic impact of the ventricular folds in computational larynx models. Journal of the Acoustical Society of America 145, 4 (2019) 2376–2387. [CrossRef] [PubMed] [Google Scholar]
  28. S. Falk, S. Kniesburges, S. Schoder, B. Jakubaß, P. Maurerlehner, M. Echternach, M. Kaltenbacher, M. Döllinger: 3D-FV-FE aeroacoustic larynx model for investigation of functional based voice disorders. Frontiers in Physiology 12 (2021) 616985. [CrossRef] [PubMed] [Google Scholar]
  29. M. Lasota, P. Šidlof, M. Kaltenbacher, S. Schoder: Impact of the subgrid-scale turbulence model in aeroacoustic simulation of human voice. Applied Sciences 11, 4 (2021) 1970. [CrossRef] [Google Scholar]
  30. M. Lasota, P. Šidlof, P. Maurerlehner, M. Kaltenbacher, S. Schoder: Anisotropic minimum dissipation subgrid-scale model in hybrid aeroacoustic simulations of human phonation. The Journal of the Acoustical Society of America 153, 2 (2023) 1052–1063. [CrossRef] [PubMed] [Google Scholar]
  31. M. Mihaescu, S.M. Khosla, S. Murugappan, E.J. Gutmark: Vortex dipolar structures in a rigid model of the larynx at flow onset. Journal of the Acoustical Society of America 127, 1 (2010) 435–444. [CrossRef] [PubMed] [Google Scholar]
  32. N.E. Chisari, G. Artana, D. Sciamarella: Vortex dipolar structures in a rigid model of the larynx at flow onset. Experiments in Fluids 50 (2011) 397–406. [CrossRef] [Google Scholar]
  33. M.H. Farahani, J. Mousel, F. Alipour, S. Vigmostad: A numerical and experimental investigation of the effect of false vocal fold geometry on glottal flow. Journal of Biomechanical Engineering 135, 12 (2013) 1210061. [CrossRef] [Google Scholar]
  34. W. Mattheus, C. Brücker: Asymmetric glottal jet deflection: Differences of two- and three-dimensional models. JASA-EL 130 (6) (2011) EL373–EL379. [CrossRef] [PubMed] [Google Scholar]
  35. S. Zörner, M. Kaltenbacher, M. Döllinger: Investigation of prescribed movement in fluid-structure interaction simulation for the human phonation process. Computers & Fluids 86 (2013) 133–140. [CrossRef] [PubMed] [Google Scholar]
  36. Y. Jo, H. Ra, Y.J. Moon, M. Döllinger: Three-dimensional computation of flow and sound for human hemilarynx. Computers & Fluids 134–135 (2016) 41–50. [CrossRef] [Google Scholar]
  37. A.G. Siemens: Simcenter STAR-CCM+, 2023. https://www.plm.automation.siemens.com/global/en/products/simcenter/STAR-CCM.html. [Google Scholar]
  38. J. Donea, A. Huerta, J-Ph Ponthot, A. Rodríguez-Ferran: Arbitrary Lagrangian-Eulerian methods, in: The Encyclopedia of Computational Mechanics, Vol. 1, John Wiley & Sons Ltd, 2004, pp. 414–437. [Google Scholar]
  39. H. Hadzic: Development and application of finite volume method for the computation of flows around moving bodies on unstructured, overlapping grids. PhD thesis, Hamburg University of Technology, 2006. [Google Scholar]
  40. J.L. Steger, F.C. Dougherty, J.A. Benek: A chimera grid scheme. [multiple overset body-conforming mesh system for finite difference adaptation to complex aircraft configurations]. Advances in Grid Generation (1983) 59–69. [Google Scholar]
  41. K. Ishizaka: Fluid mechanical considerations of vocal cord vibration. Speech Communication Research Lab, Santa Barbara, 1972. [Google Scholar]
  42. X. Pelorson, A. Hirschberg, R.R. Van Hassel, A.P.J. Wijnands, Y. Auregan: Theoretical and experimental study of quasisteady-flow separation within the glottis during phonation. Application to a modified two-mass model. Journal of the Acoustical Society of America 96, 6 (1994) 3416–3431. [CrossRef] [Google Scholar]
  43. S. Schoder, M. Weitz, P. Maurerlehner, A. Hauser, S. Falk, S. Kniesburges, M. Döllinger, M. Kaltenbacher: Hybrid aeroacoustic approach for the efficient numerical simulation of human phonation. Journal of the Acoustical Society of America 147, 2 (2020) 1179–1194. [CrossRef] [PubMed] [Google Scholar]
  44. S. Schoder, P. Maurerlehner, A. Wurzinger, A. Hauser, S. Falk, S. Kniesburges, M. Döllinger, M. Kaltenbacher: Aeroacoustic sound source characterization of the human voice production-perturbed convective wave equation. Applied Sciences 11, 6 (2021) 2614. [CrossRef] [Google Scholar]
  45. P. Maurerlehner, S. Schoder, C. Freidhager, A. Wurzinger, A. Hauser, F. Kraxberger, S. Falk, S. Kniesburges, M. Echternach, M. Döllinger, M. Kaltenbacher: Efficient numerical simulation of the human voice. e & i Elektrotechnik und Informationstechnik 138, 3 (2021) 219–228. [CrossRef] [Google Scholar]
  46. S. Schoder, F. Kraxberger, S. Falk, A. Wurzinger, K. Roppert, S. Kniesburges, M. Döllinger, M. Kaltenbacher: Error detection and filtering of incompressible flow simulations for aeroacoustic predictions of human voice. Journal of the Acoustical Society of America 152, 3 (2022) 1425–1436. [CrossRef] [PubMed] [Google Scholar]
  47. S. Schoder, K. Roppert: openCFS: Open source finite element software for coupled field simulation – part acoustics, 2022. Arxiv preprint arXiv:2207.04443. [Google Scholar]
  48. M.J. Lighthill: On sound generated aerodynamically I. General theory. Proceedings of the Royal Society of London. Series A. Mathematical and Physical Sciences 211, 1107 (1952) 564–587. [Google Scholar]
  49. R. Ewert, W. Schröder: Acoustic perturbation equations based on flow decomposition via source filtering. Journal of Computational Physics 188, 2 (2003) 365–398. [Google Scholar]
  50. P. Maurerlehner, S. Schoder, J. Tieber, C. Freidhager, H. Steiner, G. Brenn, K.H. Schäfer, A. Ennemoser, M. Kaltenbacher: Aeroacoustic formulations for confined flows based on incompressible flow data. Acta Acustica 6 (2022) 45. [CrossRef] [EDP Sciences] [Google Scholar]
  51. S. Schoder: PCWE for FSAI – Derivation of scalar wave equations for fluid-structure-acoustics interaction of low Mach number flows. 2023. arXiv preprint arXiv:2211.07490. [Google Scholar]
  52. J. Piepiorka, O. von Estorff: Numerical investigation of hydrodynamic/acoustic splitting methods in finite volumes including rotating domains, in ICA 2019 23rd international congress on acoustics, Universitätsbibliothek der RWTH Aachen, 2019. [Google Scholar]
  53. S. Schoder, M. Kaltenbacher, É. Spieser, H. Vincent, C. Bogey, C. Bailly: Aeroacoustic wave equation based on Pierce’s operator applied to the sound generated by a mixing layer, in 28th AIAA/CEAS Aeroacoustics 2022 Conference. 2022, 2896. [Google Scholar]
  54. P. Sváček, J. Horáček: Finite element approximation of flow induced vibrations of human vocal folds model: Effects of inflow boundary conditions and the length of subglottal and supraglottal channel on phonation onset. Applied Mathematics and Computation 319 (2018) 178–194. [CrossRef] [Google Scholar]
  55. A. Yang, M. Stingl, D.A. Berry, J. Lohscheller, D. Voigt, U. Eysholdt, U. Döllinger, M. Döllinger: Computation of physiological human vocal fold parameters by mathematical optimization of a biomechanical model. Journal of the Acoustical Society of America 130, 2 (2011) 948–964. [CrossRef] [PubMed] [Google Scholar]
  56. W. Jiang, C. Farbos de Luzan, X. Wang, L. Oren, S.M. Khosla, Q. Xue, X. Zheng: Computational modeling of voice production using excised canine larynx, Journal of Biomechanical Engineering 144, 2 (2022) 021003. [CrossRef] [PubMed] [Google Scholar]
  57. S.L. Smith, S.L. Thomson: Effect of inferior surface angle on the self-oscillation of a computational vocal fold model. Journal of the Acoustical Society of America 131, 5 (2012) 4062–4075. [CrossRef] [PubMed] [Google Scholar]
  58. M. Feistauer, P. Sváček, J. Horáček: Numerical simulation of fluid-structure interaction problems with applications to flow in vocal folds, in: T. Bodnár, G. Galdi, Š. Nečasová (Eds.), Fluid-structure interaction and biomedical applications, Advances in Mathematical Fluid Mechanics, Springer, Basel, 2014, pp. 321–393. https://doi.org/10.1007/978-3-0348-0822-4_5. [CrossRef] [Google Scholar]
  59. R. Mittal, G. Iaccarino: Immersed boundary methods. Annual Review of Fluid Mechanics 37, 1 (2005) 239–261. [CrossRef] [Google Scholar]
  60. H. Luo, R. Mittal, S.A. Bielamowicz: Analysis of flow-structure interaction in the larynx during phonation using an immersed-boundary method. Journal of the Acoustical Society of America 126, 2 (2009) 816–824. [CrossRef] [PubMed] [Google Scholar]
  61. J.H. Seo, R. Mittal: A high-order immersed boundary method for acoustic wave scattering and low-Mach number flow-induced sound in complex geometries. Journal of Computational Physics 230, 4 (2011) 1000–1019. [CrossRef] [PubMed] [Google Scholar]
  62. G. Link, M. Kaltenbacher, M. Breuer, M. Döllinger: A 2D finite-element scheme for fluid–solid–acoustic interactions and its application to human phonation. Computer Methods in Applied Mechanics and Engineering 198, 41–44 (2009) 3321–3334. [CrossRef] [Google Scholar]
  63. G.Z. Decker, S.L. Thomson: Computational simulations of vocal fold vibration: Bernoulli versus Navier-Stokes. Journal of Voice 21, 3 (2007) 273–284. [CrossRef] [PubMed] [Google Scholar]
  64. D.J. Daily, S.L. Thomson: Acoustically-coupled flow-induced vibration of a computational vocal fold model. Computers & Structures 116 (2013) 50–58. [CrossRef] [PubMed] [Google Scholar]
  65. B.H. Story: A parametric model of the vocal tract area function for vowel and consonant simulation. Journal of the Acoustical Society of America 117, 5 (2005) 3231–3254. [CrossRef] [PubMed] [Google Scholar]
  66. B.H. Story, I.R. Titze, E.A. Hoffman: Vocal tract area functions from magnetic resonance imaging. Journal of the Acoustical Society of America 100, 1 (1996) 537–554. [CrossRef] [PubMed] [Google Scholar]
  67. W. Jiang, X. Zheng, Q. Xue: Computational modeling of fluid–structure–acoustics interaction during voice production. Frontiers in Bioengineering and Biotechnology 5 (2017) 7. [CrossRef] [PubMed] [Google Scholar]
  68. W. Jiang, Q. Xue, X. Zheng: Effect of longitudinal variation of vocal fold inner layer thickness on fluid-structure interaction during voice production. Journal of Biomechanical Engineering 140, 12 (2018) 1210081–1210089. [CrossRef] [PubMed] [Google Scholar]
  69. D. Bodaghi, Q. Xue, X. Zheng, S.L. Thomson: Effect of subglottic stenosis on vocal fold vibration and voice production using fluid–structure–acoustics interaction simulation. Applied Sciences 11, 3 (2021) 1221. [CrossRef] [Google Scholar]
  70. D. Bodaghi, W. Jiang, Q. Xue, X. Zheng: Effect of supraglottal acoustics on fluid-structure interaction during human voice production. Journal of Biomechanical Engineering 143, 4 (2021) 041010. [CrossRef] [PubMed] [Google Scholar]
  71. A. Yang, D.A. Berry, M. Kaltenbacher, M. Döllinger: Three-dimensional biomechanical properties of human vocal folds: parameter optimization of a numerical model to match in vitro dynamics. Journal of the Acoustical Society of America 131, 2 (2012) 1378–1390. [CrossRef] [PubMed] [Google Scholar]
  72. M. Döllinger, P. Gomez, R.R. Patel, C. Alexiou, C. Bohr, A. Schützenberger: Biomechanical simulation of vocal fold dynamics in adults based on laryngeal high-speed videoendoscopy. PloS One 12, 11 (2017) e0187486. [CrossRef] [PubMed] [Google Scholar]
  73. J. Neubauer, Z. Zhang, R. Miraghaie, D.A. Berry: Coherent structures of the near field flow in a self-oscillating physical model of the vocal folds. Journal of the Acoustical Society of America 121, 2 (2007) 1102–1118. [CrossRef] [PubMed] [Google Scholar]
  74. M. Triep, C. Brücker: Three-dimensional nature of the glottal jet. Journal of the Acoustical Society of America 127, 3 (2010) 1537–1547. [CrossRef] [PubMed] [Google Scholar]
  75. L. Oren, S. Khosla, E. Gutmark: Intraglottal geometry and velocity measurements in canine larynges. Journal of the Acoustical Society of America 135, 1 (2014) 380–388. [CrossRef] [PubMed] [Google Scholar]
  76. Z. Zhang, J. Neubauer: On the acoustical relevance of supraglottal flow structures to low-frequency voice production. Journal of the Acoustical Society of America 128, 6 (2010) EL378–EL383. [CrossRef] [PubMed] [Google Scholar]
  77. M.H. Farahani, Z. Zhang: A computational study of the effect of intraglottal vortex-induced negative pressure on vocal fold vibration. Journal of the Acoustical Society of America 136, 5 (2014) EL369–EL375. [CrossRef] [PubMed] [Google Scholar]
  78. A. Pirnia, E.A. Browning, S.D. Peterson, B.D. Erath: Discrete and periodic vortex loading on a flexible plate; application to energy harvesting and voiced speech production. Journal of Sound and Vibration 433 (2018) 476–492. [CrossRef] [Google Scholar]
  79. B.Q. Kettlewell: The influence of intraglottal vortices upon the dynamics of the vocal folds. Master’s thesis, University of Waterloo, 2015. [Google Scholar]
  80. Z. Li, Y. Chen, S. Chang, H. Luo: A reduced-order flow model for fluid–structure interaction simulation of vocal fold vibration. Journal of Biomechanical Engineering 142, 2 (2020) 0210051–02100510. [PubMed] [Google Scholar]
  81. Y. Chen, Z. Li, S. Chang, B. Rousseau, H. Luo: A reduced-order flow model for vocal fold vibration: From idealized to subject-specific models. Journal of Fluids and Structures 94 (2020) 102940. [CrossRef] [PubMed] [Google Scholar]
  82. Z. Li, Y. Chen, S. Chang, B. Rousseau, H. Luo: A one-dimensional flow model enhanced by machine learning for simulation of vocal fold vibration. Journal of the Acoustical Society of America 149, 3 (2021) 1712–1723. [CrossRef] [PubMed] [Google Scholar]
  83. T. Yoshinaga, Z. Zhang, A. Iida: Comparison of one-dimensional and three-dimensional glottal flow models in left-right asymmetric vocal fold conditions. Journal of the Acoustical Society of America 152, 5 (2022) 2557–2569. [CrossRef] [PubMed] [Google Scholar]
  84. N. Ruty, X. Pelorson, A. Van Hirtum, I. Lopez-Arteaga, A. Hirschberg: An in vitro setup to test the relevance and the accuracy of low-order vocal folds models. Journal of the Acoustical Society of America 121, 1 (2007) 479–490. [CrossRef] [PubMed] [Google Scholar]
  85. T. Kaburagi, Y. Tanabe: Low-dimensional models of the glottal flow incorporating viscous-inviscid interaction. Journal of the Acoustical Society of America 125, 1 (2009) 391–404. [CrossRef] [PubMed] [Google Scholar]
  86. M.H. Farahani, Z. Zhang: Experimental validation of a three-dimensional reduced-order continuum model of phonation. Journal of the Acoustical Society of America 140, 2 (2016) EL172–EL177. [CrossRef] [PubMed] [Google Scholar]
  87. J.E. Kelleher, T. Siegmund, M. Du, E. Naseri, R.W. Chan: The anisotropic hyperelastic biomechanical response of the vocal ligament and implications for frequency regulation: A case study. Journal of the Acoustical Society of America 133, 3 (2013) 1625–1636. [CrossRef] [PubMed] [Google Scholar]
  88. A.K. Miri, H.K. Heris, U. Tripathy, P.W. Wiseman, L. Mongeau: Microstructural characterization of vocal folds toward a strain-energy model of collagen remodeling. Acta Biomaterialia 9, 8 (2013) 7957–7967. [CrossRef] [PubMed] [Google Scholar]
  89. Z. Zhang Structural constitutive modeling of the anisotropic mechanical properties of human vocal fold lamina propria, Journal of the Acoustical Society of America 145, 6 (2019) EL476–EL482. [CrossRef] [PubMed] [Google Scholar]
  90. A. Terzolo, L. Bailly, L. Orgéas, T. Cochereau, N. Henrich-Bernardoni: A micro-mechanical model for the fibrous tissues of vocal folds. Journal of the Mechanical Behavior of Biomedical Materials 128 (2022) 105118. [CrossRef] [PubMed] [Google Scholar]
  91. I.R. Titze, D.T. Talkin: A theoretical study of the effects of various laryngeal configurations on the acoustics of phonation. Journal of the Acoustical Society of America 66, 1 (1979) 60–74. [CrossRef] [PubMed] [Google Scholar]
  92. Q. Xue, X. Zheng, R. Mittal, S. Bielamowicz: Subject-specific computational modeling of human phonation. Journal of the Acoustical Society of America 135, 3 (2014) 1445–1456. [CrossRef] [PubMed] [Google Scholar]
  93. L. Wu, Z. Zhang: Voice production in a MRI-based subject-specific vocal fold model with parametrically controlled medial surface shape. The Journal of the Acoustical Society of America 146, 6 (2019) 4190–4198. [CrossRef] [PubMed] [Google Scholar]
  94. S. Chang, F.B. Tian, H. Luo, J.F. Doyle, B. Rousseau: The role of finite displacements in vocal fold modeling. Journal of Biomechanical Engineering 135, 11 (2013) 111008. [CrossRef] [PubMed] [Google Scholar]
  95. Z. Zhang: Regulation of glottal closure and airflow in a three-dimensional phonation model: Implications for vocal intensity control. Journal of the Acoustical Society of America 137, 2 (2015) 898–910. [CrossRef] [PubMed] [Google Scholar]
  96. Z. Zhang: Toward real-time physically-based voice simulation: An eigenmode-based approach, in Proceedings of Meetings on Acoustics 173EAA(1). Acoustical Society of America (2017) 060002. [CrossRef] [Google Scholar]
  97. Z. Zhang: Cause-effect relationship between vocal fold physiology and voice production in a three-dimensional phonation model. Journal of the Acoustical Society of America 139, 4 (2016) 1493–1507. [CrossRef] [PubMed] [Google Scholar]
  98. Z. Zhang: Effect of vocal fold stiffness on voice production in a three-dimensional body-cover phonation model. Journal of the Acoustical Society of America 142, 4 (2017) 2311–2321. [CrossRef] [PubMed] [Google Scholar]
  99. Z. Zhang: Contribution of laryngeal size to differences between male and female voice production. Journal of the Acoustical Society of America 150, 6 (2021) 4511–4521. [CrossRef] [PubMed] [Google Scholar]
  100. L. Wu, Z. Zhang: Impact of the paraglottic space on voice production in an MRI-based vocal fold model. Journal of Voice (2021) https://doi.org/10.1016/j.jvoice.2021.02.021. [Google Scholar]
  101. Z. Zhang, T. Hieu Luu: Asymmetric vibration in a two-layer vocal fold model with left-right stiffness asymmetry: Experiment and simulation. Journal of the Acoustical Society of America 132, 3 (2012) 1626–1635. [CrossRef] [PubMed] [Google Scholar]
  102. P. Gómez, A. Schützenberger, S. Kniesburges, C. Bohr, M. Döllinger: Physical parameter estimation from porcine ex vivo vocal fold dynamics in an inverse problem framework. Biomechanics and Modeling in Mechanobiology 17, 3 (2018) 777–792. [CrossRef] [PubMed] [Google Scholar]
  103. M. Kunduk, M. Döllinger, A. McWhorter, J. Lohscheller: Assessment of the variability of vocal fold dynamics with and between recordings with high-speed imaging and by Phonovibrogram. Laryngoscope 120, 5 (2010) 981–987. [CrossRef] [PubMed] [Google Scholar]
  104. M. Döllinger, T. Braunschweig, J. Lohscheller, U. Eysholdt, U. Hoppe: Normal voice production: computation of driving parameters from endoscopic digital high speed images. Methods of Information in Medicine 42 (2003) 271–276. [CrossRef] [PubMed] [Google Scholar]
  105. P.J. Hadwin, S.D. Peterson: An extended Kalman filter approach to non-stationary Bayesian estimation of reduced-order vocal fold model parameters. Journal of the Acoustical Society of America 141, 4 (2017) 2909–2920. [CrossRef] [PubMed] [Google Scholar]
  106. P. Gomez, M. Semmler, C. Bohr, M. Döllinger: Laryngeal pressure estimation with a recurrent neural network. IEEE Journal of Translational Engineering in Health and Medicine 7 (2019) 8590726. [CrossRef] [Google Scholar]
  107. R.R. Patel, D. Dubrovskiy, M. Döllinger: Characterizing vibratory kinematics in children and adults with high-speed digital imaging. Journal of Speech, Language, and Hearing Research 57, 2 (2014) 674–686. [CrossRef] [Google Scholar]
  108. A.M. Kist, J. Zilker, P. Gómez, A. Schützenberger, M. Döllinger: Rethinking glottal midline detection. Scientfic Reports 10, 1 (2020) 20723. [CrossRef] [Google Scholar]
  109. Z. Li, S. Chang, B. Rousseau, H. Luo: A one-dimensional flow model enhanced by machine learning for simulation of vocal fold vibration. Journal of the Acoustical Society of America 149, 3 (2021) 1712–1723. [CrossRef] [PubMed] [Google Scholar]
  110. Y. Zhang, W. Jiang, L. Sun, J. Wang, X. Zheng, Q. Xue: A deep-learning based generalized empirical flow model of glottal flow during normal phonation. Journal of Biomechanical Engineering 144, 9 (2022) 091001. [PubMed] [Google Scholar]
  111. Y. Zhang, T. Pu, C. Zhou, H. Cai: An improved glottal flow model based on Seq2Seq LSTM for simulation of vocal fold vibration. Journal of Voice (2022) S0892–1997(22). [Google Scholar]
  112. Z. Zhang: Estimation of vocal fold physiology from voice acoustics using machine learning. Journal of the Acoustical Society of America 147(3), (2020)EL264–EL270. [CrossRef] [PubMed] [Google Scholar]
  113. Z. Zhang: Voice feature selection to improve performance of machine learning models for voice production inversion. Journal of Voice (2021). https://doi.org/10.1016/j.jvoice.2021.03.004. [Google Scholar]
  114. Z. Zhang: Estimating subglottal pressure and vocal fold adduction from the produced voice in a single-subject study (L). Journal of the Acoustical Society of America 151, 2 (2022) 1337–1340. [CrossRef] [PubMed] [Google Scholar]
  115. I.R. Titze, J.C. Lucero: Voice simulation: the next generation. Applied Sciences 12, 22 (2022) 11720. [CrossRef] [Google Scholar]
  116. R. Schwarze, W. Mattheus, J. Klostermann, C. Brücker: Starting jet flows in a three-dimensional channel with larynx-shaped constriction. Computers & Fluids 48 (2011) 68–83. [CrossRef] [Google Scholar]
  117. S.L. Thomson, L. Mongeau, S.H. Frankel: Aerodynamic transfer of energy to the vocal folds. Journal of the Acoustical Society of America 118, 3 (2005) 1689–1700. [CrossRef] [PubMed] [Google Scholar]
  118. B.H. Story, I.R. Titze: Voice simulation with a body-cover model of the vocal folds. Journal of the Acoustical Society of America 97, 2 (1995) 1249–1260. [CrossRef] [PubMed] [Google Scholar]

Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.

Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.

Initial download of the metrics may take a while.