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Dabbaghchian, S., Arnela, M., Engwall, O. & Guasch, O. (2018). Reconstruction of vocal tract geometries from biomechanical simulations. International Journal for Numerical Methods in Biomedical Engineering
Open this publication in new window or tab >>Reconstruction of vocal tract geometries from biomechanical simulations
2018 (English)In: International Journal for Numerical Methods in Biomedical Engineering, ISSN 2040-7939, E-ISSN 2040-7947Article in journal (Refereed) Published
Abstract [en]

Medical imaging techniques are usually utilized to acquire the vocal tract geometry in 3D, which may then be used, eg, for acoustic/fluid simulation. As an alternative, such a geometry may also be acquired from a biomechanical simulation, which allows to alter the anatomy and/or articulation to study a variety of configurations. In a biomechanical model, each physical structure is described by its geometry and its properties (such as mass, stiffness, and muscles). In such a model, the vocal tract itself does not have an explicit representation, since it is a cavity rather than a physical structure. Instead, its geometry is defined implicitly by all the structures surrounding the cavity, and such an implicit representation may not be suitable for visualization or for acoustic/fluid simulation. In this work, we propose a method to reconstruct the vocal tract geometry at each time step during the biomechanical simulation. Complexity of the problem, which arises from model alignment artifacts, is addressed by the proposed method. In addition to the main cavity, other small cavities, including the piriform fossa, the sublingual cavity, and the interdental space, can be reconstructed. These cavities may appear or disappear by the position of the larynx, the mandible, and the tongue. To illustrate our method, various static and temporal geometries of the vocal tract are reconstructed and visualized. As a proof of concept, the reconstructed geometries of three cardinal vowels are further used in an acoustic simulation, and the corresponding transfer functions are derived.

Place, publisher, year, edition, pages
John Wiley & Sons, 2018
National Category
Computer Sciences
Research subject
Speech and Music Communication
Identifiers
urn:nbn:se:kth:diva-239055 (URN)10.1002/cnm.3159 (DOI)000458548700001 ()
Funder
EU, FP7, Seventh Framework Programme, 308874
Note

QC 20181116

Available from: 2018-11-15 Created: 2018-11-15 Last updated: 2019-04-04Bibliographically approved
Dabbaghchian, S., Arnela, M., Engwall, O. & Guasch, O. (2018). Synthesis of vowels and vowel-vowel utterancesusing a 3D biomechanical-acoustic model. IEEE/ACM Transactions on Audio, Speech, and Language Processing
Open this publication in new window or tab >>Synthesis of vowels and vowel-vowel utterancesusing a 3D biomechanical-acoustic model
2018 (English)In: IEEE/ACM Transactions on Audio, Speech, and Language Processing, ISSN 2329-9290Article in journal (Refereed) Submitted
Abstract [en]

A link is established between a 3D biomechanicaland acoustic model allowing for the umerical synthesis of vowelsounds by contraction of the relevant muscles. That is, thecontraction of muscles in the biomechanical model displacesand deforms the articulators, which in turn deform the vocaltract shape. The mixed wave equation for the acoustic pressureand particle velocity is formulated in an arbitrary Lagrangian-Eulerian framework to account for moving boundaries. Theequations are solved numerically using the finite element method.Since the activation of muscles are not fully known for a givenvowel sound, an inverse method is employed to calculate aplausible activation pattern. For vowel-vowel utterances, two different approaches are utilized: linear interpolation in eithermuscle activation or geometrical space. Although the former isthe natural choice for biomechanical modeling, the latter is usedto investigate the contribution of biomechanical modeling onspeech acoustics. Six vowels [ɑ, ə, ɛ, e, i, ɯ] and three vowel-vowelutterances [ɑi, ɑɯ, ɯi] are synthesized using the 3D model. Results,including articulation, formants, and spectrogram of vowelvowelsounds, are in agreement with previous studies.Comparingthe spectrogram of interpolation in muscle and geometrical spacereveals differences in all frequencies, with the most extendeddifference in the second formant transition.

National Category
Computer Sciences
Research subject
Speech and Music Communication
Identifiers
urn:nbn:se:kth:diva-239056 (URN)
Projects
EUNISON
Funder
EU, FP7, Seventh Framework Programme, 308874
Note

QC 20181116

Available from: 2018-11-15 Created: 2018-11-15 Last updated: 2018-11-16Bibliographically approved
Arnela, M., Dabbaghchian, S., Guasch, O. & Engwall, O. (2017). A semi-polar grid strategy for the three-dimensional finite element simulation of vowel-vowel sequences. In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017: . Paper presented at 18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017 (pp. 3477-3481). The International Speech Communication Association (ISCA), 2017
Open this publication in new window or tab >>A semi-polar grid strategy for the three-dimensional finite element simulation of vowel-vowel sequences
2017 (English)In: Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, The International Speech Communication Association (ISCA), 2017, Vol. 2017, p. 3477-3481Conference paper, Published paper (Refereed)
Abstract [en]

Three-dimensional computational acoustic models need very detailed 3D vocal tract geometries to generate high quality sounds. Static geometries can be obtained from Magnetic Resonance Imaging (MRI), but it is not currently possible to capture dynamic MRI-based geometries with sufficient spatial and time resolution. One possible solution consists in interpolating between static geometries, but this is a complex task. We instead propose herein to use a semi-polar grid to extract 2D cross-sections from the static 3D geometries, and then interpolate them to obtain the vocal tract dynamics. Other approaches such as the adaptive grid have also been explored. In this method, cross-sections are defined perpendicular to the vocal tract midline, as typically done in 1D to obtain the vocal tract area functions. However, intersections between adjacent cross-sections may occur during the interpolation process, especially when the vocal tract midline quickly changes its orientation. In contrast, the semi-polar grid prevents these intersections because the plane orientations are fixed over time. Finite element simulations of static vowels are first conducted, showing that 3D acoustic wave propagation is not significantly altered when the semi-polar grid is used instead of the adaptive grid. The vowel-vowel sequence [ɑi] is finally simulated to demonstrate the method.

Place, publisher, year, edition, pages
The International Speech Communication Association (ISCA), 2017
Series
Proceedings of the Annual Conference of the International Speech Communication Association, INTERSPEECH, ISSN 2308-457X ; 2017
National Category
Language Technology (Computational Linguistics)
Research subject
Speech and Music Communication
Identifiers
urn:nbn:se:kth:diva-212994 (URN)10.21437/Interspeech.2017-448 (DOI)000457505000724 ()2-s2.0-85039147985 (Scopus ID)
Conference
18th Annual Conference of the International Speech Communication Association, INTERSPEECH 2017, Stockholm, Sweden, 20 August 2017 through 24 August 2017
Note

QC 20170828

Available from: 2017-08-25 Created: 2017-08-25 Last updated: 2019-09-24Bibliographically approved
Dabbaghchian, S., Nilsson, I. & Engwall, O. (2014). From Tongue Movement Data to Muscle Activation – A Preliminary Study of Artisynth's Inverse Modelling. In: : . Paper presented at Parametric Modeling of Human Anatomy, PMHA 14, Aug 22-23, 2014, Vancouver, BC, CA.
Open this publication in new window or tab >>From Tongue Movement Data to Muscle Activation – A Preliminary Study of Artisynth's Inverse Modelling
2014 (English)Conference paper, Published paper (Other academic)
Abstract [en]

Finding the muscle activations during speech production is an important part of developing a comprehensive biomechanical model of speech production. Although there are some direct ways, like Electromyography, for measuring muscle activations, these methods usually are highly invasive and sometimes not reliable. They are more over impossible to use for all muscles. In this study we therefore explore an indirect way to estimate tongue muscle activations during speech production by combining Electromagnetic Articulography (EMA) measurements of tongue movements and the inverse modeling in Artisynth. With EMA we measure the time-changing 3D positions of four sensors attached to the tongue surface for a Swedish female subject producing vowel-vowel and vowelconsonant-vowel (VCV) sequences. The measured sensor positions are used as target points for corresponding virtual sensors introduced in the tongue model of Artisynth’s inverse modelling framework, which computes one possible combination of muscle activations that results in the observed sequence of tongue articulations. We present resynthesized tongue movements in the Artisynth model and verify the results by comparing the calculated muscle activations with literature.

Keywords
speech, tongue, muscle activation, electromagnetic articulography, biomechanics
National Category
Computer Sciences
Identifiers
urn:nbn:se:kth:diva-239054 (URN)
Conference
Parametric Modeling of Human Anatomy, PMHA 14, Aug 22-23, 2014, Vancouver, BC, CA
Funder
EU, FP7, Seventh Framework Programme, 308874
Note

QC 20181116

Available from: 2018-11-15 Created: 2018-11-15 Last updated: 2018-11-16Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0003-4532-014X

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