15 research outputs found

    Influences of tongue biomechanics on speech movements during the production of velar stop consonants: a modeling study

    Get PDF
    This study explores the following hypothesis: forward looping movements of the tongue that are observed in VCV sequences are due partly to the anatomical arrangement of the tongue muscles and how they are used to produce a velar closure. The study uses an anatomically based 2D biomechanical tongue model. Tissue elastic properties are accounted for in finite-element modeling, and movement is controlled by constant-rate control parameter shifts. Tongue raising and lowering movements are produced by the model with the combined actions of the genioglossus, styloglossus and hyoglossus. Simulations of V1CV2 movements were made, where C is a velar consonant and V is [a], [i] or [u]. If V1 is one of the vowels [a] and [u], the resulting trajectories describe movements that begin to loop forward before consonant closure and continue to slide along the palate during the closure. This prediction is in agreement with classical data published in the literature. If V1 is vowel [i], we observe a small backward movement. This is also in agreement with some measurements on human speakers, but it is also in contradiction with the original data published by Houde (1967). These observations support the idea that the biomechanical properties of the tongue could be the main factor responsible for the forward loops when V1 is a back vowel. In the left [i] context, it seems that additional factors have to be taken into considerations, in order to explain the observations made on some speaker

    Speech Communication

    Get PDF
    Contains table of contents for Part V, table of contents for Section 1, reports on six research projects and a list of publications.C.J. Lebel FellowshipDennis Klatt Memorial FundNational Institutes of Health Grant R01-DC00075National Institutes of Health Grant R01-DC01291National Institutes of Health Grant R01-DC01925National Institutes of Health Grant R01-DC02125National Institutes of Health Grant R01-DC02978National Institutes of Health Grant R01-DC03007National Institutes of Health Grant R29-DC02525National Institutes of Health Grant F32-DC00194National Institutes of Health Grant F32-DC00205National Institutes of Health Grant T32-DC00038National Science Foundation Grant IRI 89-05249National Science Foundation Grant IRI 93-14967National Science Foundation Grant INT 94-2114

    Efficient 3D Finite Element Modeling of a Muscle-Activated Tongue

    No full text
    We describe our investigation of a fast 3D finite element method (FEM) for biomedical simulation of a muscle-activated human tongue. Our method uses a linear stiffness-warping scheme to achieve simulation speeds which are within a factor 10 of real-time rates at the expense of a small loss in accuracy. Muscle activations are produced by an arrangement of forces acting along selected edges of the FEM geometry. The model's dynamics are integrated using an implicit Euler formulation, which can be solved using either the conjugate gradient method or a direct sparse solver. To assess the utility of this model, we compare its accuracy against slower, but less approximate, simulations of a reference tongue model prepared using the FEM simulation package ANSYS

    The Distributed Lambda (λ) Model (DLM): A 3-D, Finite-Element Muscle Model Based on Feldman's λ Model; Assessment of Orofacial Gestures

    No full text
    International audiencePurpose: The authors aimed to design a distributed Lambda model (DLM), which is well-adapted to implement three-dimensional (3-D) Finite Element descriptions of muscles. Method: A muscle element model was designed. Its stress-strain relationships included the active force-length characteristics of the Lambda model along the muscle fibers, together with the passive properties of muscle tissues in the 3-D space. The muscle element was first assessed using simple geometrical representations of muscles in form of rectangular bars. Then, it was included in a 3-D face model, and its impact on lip protrusion was compared with the impact of a Hill-type muscle model. Results: The force-length characteristic associated with the muscle elements matched well with the invariant characteristics of the Lambda model. The impact of the passive properties was assessed. Isometric force variation and isotonic displacements were modeled. The comparison with a Hill-type model revealed strong similarities in terms of global stress and strain. Conclusion: The DLM accounted for the characteristics of the Lambda model. Biomechanically no clear differences were found between the DLM and a Hill-type model. Accurate evaluations of the Lambda model, based on the comparison between data and simulations, are now possible with 3-D biomechanical descriptions of the speech articulators because to the DLM
    corecore