20.270, Diss: Phonetics/Phonology: Baker: 'A Biomechanical Model of the ...'

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LINGUIST List: Vol-20-270. Wed Jan 28 2009. ISSN: 1068 - 4875.

Subject: 20.270, Diss: Phonetics/Phonology: Baker: 'A Biomechanical Model of the ...'

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1)
Date: 27-Jan-2009
From: Adam Baker < adamb924 at gmail.com >
Subject: A Biomechanical Model of the Human Tongue for Understanding Speech Production and other Lingual Behaviors

 

	
-------------------------Message 1 ---------------------------------- 
Date: Wed, 28 Jan 2009 12:31:54
From: Adam Baker [adamb924 at gmail.com]
Subject: A Biomechanical Model of the Human Tongue for Understanding Speech Production and other Lingual Behaviors

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Institution: University of Arizona 
Program: Department of Linguistics 
Dissertation Status: Completed 
Degree Date: 2008 

Author: Adam Baker

Dissertation Title: A Biomechanical Model of the Human Tongue for Understanding 
Speech Production and other Lingual Behaviors 

Dissertation URL:  http://apil.arizona.edu/baker/

Linguistic Field(s): Phonetics
                     Phonology


Dissertation Director(s):
Michael Hammond
Jonathan Vande Geest
Brad Story

Dissertation Abstract:

A biomechanical model of the human tongue was constructed, based upon a
detailed anatomical study of an actual cadaver. Data from the Visible Human
Project were segmented to create a volumetric representation of the tongue
and its constituent muscles. The volumetric representation was converted to
a smooth NURBS-bounded solid model - for compatibility with meshing
algorithms - by lofting between splines, the vertices of which were defined
by the coordinates of a smoothed triangular mesh representation. Using a
hyperelastic constitutive model that allowed for the addition of active
stress, the model deforms in response to user-specified muscle activation
patterns. A series of meshes was created to perform a mesh validation
study; in the validation tests performed, a 245,223-element mesh was found
to be sufficient to model tongue behavior.

Systematic samples of the behavior of the model were collected. Principal
component analyses were performed on the samples to discover
low-dimensional representations of tongue postures. Statistical models
(linear regression models and neural networks) were fit to predict tongue
posture from muscle activation, and vice versa. In all tests, it was found
that a relatively small sample of tongue postures can be used to
successfully generalize to larger data sets.

Finally, a variety of specific tests were performed, based on claims and
predictions found in previous literature. Of these, the claims of the
muscular hydrostat theory of tongue movement were best supported.
Simulations were also run that simulated lingual hemiplegia. It was found
that substantially different muscular activation patterns were required to
achieve equivalent postures in a hemiplegic tongue, relative to a normal
tongue.

The present work advances the state of tongue modeling in several respects.
It is based on a detailed anatomical study of an actual specimen. It is
also the first tongue model to have been subjected to a mesh validation
study. It is anticipated that the model will be of use in further research
into the mechanical properties of the tongue, and the relationship between
tongue muscle activation and the acoustical output of the vocal tract. 






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