A perioral dynamic model for investigating human speech articulation

A multibody system called the perioral dynamic model for investigating dynamic behavior of human speech articulator is presented. The model is based on the biomechanical architecture of human speech articulators, consisting of the soft tissue around the lips, the related muscles, and the jaw bone structure. The dynamic consequence of human speech articulation is revealed as a sequential perioral motion induced by the selectively activated muscle actions. As an anatomically consistent biomechanical platform, the perioral dynamic model is designed to represent the rigid jaw motion as well as the perioral soft tissue deformation interacting with each other. The perioral soft tissue in the model is approximated as a discrete particle system consisting of lumped point masses interconnecting with adjacent ones via viscoelastic elements. To ensure continuum-compatible static deformation in the discrete particle system, we introduce a method of adjusting element stiffness. We also present a new method for determining the effective forces acting on the jaw-bone-attached nodes that transforms jaw dynamics in the rigid body system into the one defined in the discrete particle system, keeping dynamic equivalency and equipollency between two systems. To derive muscle activations which let the developed dynamic model produce a simulated perioral motion mimicking an actual human speech behavior, we present an inverse dynamics technique driven by visual observation-based feedback of an actual lip motion.

[1]  W. Blajer,et al.  Multibody modeling of human body for the inverse dynamics analysis of sagittal plane movements , 2007 .

[2]  Olov Engwall,et al.  Are static MRI measurements representative of dynamic speech? results from a comparative study using MRI, EPG and EMA , 2000, Interspeech.

[3]  W S Levine,et al.  Modeling the motion of the internal tongue from tagged cine-MRI images. , 2001, The Journal of the Acoustical Society of America.

[4]  F. Beer.  Vector Mechanics for Engineers: Dynamics , 1950 .

[5]  Vladimir M Zatsiorsky,et al.  Optimization-Based Models of Muscle Coordination , 2002, Exercise and sport sciences reviews.

[6]  Luisa Consiglieri,et al.  Analytical approach for the evaluation of the torques using inverse multibody dynamics , 2007 .

[7]  J. Flanagan,et al.  Chapter 2 Control of Human Jaw and Multi-Joint Arm Movements , 1990 .

[8]  D. Dawe,et al.  Matrix and finite element displacement analysis of structures , 1984 .

[9]  Yohan Payan,et al.  3D biomechanical tongue modeling to study speech production , 2006 .

[10]  Hiroaki Gomi,et al.  Model-Based Investigation of Control and Dynamics in Human Articulatory Motion , 2007 .

[11]  Demetri Terzopoulos,et al.  Physically-based facial modelling, analysis, and animation , 1990, Comput. Animat. Virtual Worlds.

[12]  G. Lichtwark,et al.  Effects of series elasticity and activation conditions on muscle power output and efficiency , 2005, Journal of Experimental Biology.

[13]  M Pitermann,et al.  An inverse dynamics approach to face animation. , 2001, The Journal of the Acoustical Society of America.

[14]  Keith Waters,et al.  A muscle model for animation three-dimensional facial expression , 1987, SIGGRAPH.

[15]  W. Thomson.  Theory of vibration with applications , 1965 .

[16]  Shinji Ozawa,et al.  Generating facial expressions based on estimation of muscular contraction parameters from facial feature points , 2004, 2004 IEEE International Conference on Systems, Man and Cybernetics (IEEE Cat. No.04CH37583).

[17]  K G Munhall,et al.  A model of facial biomechanics for speech production. , 1999, The Journal of the Acoustical Society of America.

[18]  James H. Abbs,et al.  Anatomic Studies of the Perioral Motor System: Foundations for Studies in Speech Physiology , 1979 .

[19]  Yongping Zheng,et al.  Estimation of Young's modulus and Poisson's ratio of soft tissue from indentation using two different-sized indentors: Finite element analysis of the finite deformation effect , 2005, Medical and Biological Engineering and Computing.

[20]  Hiroaki Gomi,et al.  Fast force-generation dynamics of human articulatory muscles. , 2004, Journal of applied physiology.

[21]  G. Hammond.  Cerebral control of speech and limb movements , 1990 .

[22]  Shoichiro Nakamura.  Applied numerical methods with software , 1991 .

[23]  Parke,et al.  Parameterized Models for Facial Animation , 1982, IEEE Computer Graphics and Applications.

[24]  Francis A. Duck,et al.  Physical properties of tissue : a comprehensive reference book , 1990 .

[25]  Peter Eberhard,et al.  Investigations for the Dynamical Analysis of Human Motion , 1999 .

[26]  William H. Press,et al.  Numerical Recipes: FORTRAN , 1988 .

[27]  Yu Zhang,et al.  A new physical model with multilayer architecture for facial expression animation using dynamic adaptive mesh , 2004, IEEE Transactions on Visualization and Computer Graphics.

[28]  Demetri Terzopoulos,et al.  Analysis and Synthesis of Facial Image Sequences Using Physical and Anatomical Models , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[29]  P. Venkataraman,et al.  Applied Optimization with MATLAB Programming , 2001 .

[30]  Demetri Terzopoulos,et al.  Realistic modeling for facial animation , 1995, SIGGRAPH.

[31]  B. Nigg,et al.  Modification of soft tissue vibrations in the leg by muscular activity. , 2001, Journal of applied physiology.

[32]  Frederick I. Parke,et al.  Computer generated animation of faces , 1972, ACM Annual Conference.

[33]  A. Hill.  The heat of shortening and the dynamic constants of muscle , 1938 .

[34]  Tadashi Kashima,et al.  An optimal control model of a neuromuscular system in human arm movements and its control characteristics , 2006, Artificial Life and Robotics.

[35]  David J. Ostry,et al.  The control of multi-muscle systems: human jaw and hyoid movements , 1996, Biological Cybernetics.