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Abstract #4151

Semi-automatically tracking articulatory features in 2D dynamic sagittal MRI images

Jiyoon Kim1,2, Laura Spinu3, Jonghye Woo4, Fangxu Xing4, Jamie Perry5, Imani Gilbert5, and Bradley P Sutton1,2
1Bioengineering, University of Illinois at Urbana-Champaign, Champaign, IL, United States, 2Beckman Institute for Advanced Science and Technology, University of Illinois Urbana-Champaign, Urbana, IL, United States, 3Department of Communications & Performing Arts, The City University of New York, New York, NY, United States, 4Gordon Center for Medical Imaging, Department of Radiology, Massachusetts General Hospital/Harvard Medical School, Boston, MA, United States, 5Department of Communication Sciences and Disorders, East Carolina University, Greenville, NC, United States

Synopsis

Keywords: Data Processing, Analysis/Processing, Speech analysis

Motivation: The motivation for this research is from the need to improve diagnosis and treatment of speech disorders, as well as advancements in speech synthesis.

Goal(s): By analyzing the movement of the lips, tongue and velum during speech, we aim to gain insights into the coordination required for accurate pronunciation.

Approach: UsUsing coordinate data from corresponding frames of the corresponding phrase across five samples, we measure y-coordinate difference, calculating the velocity for the feature's movements.

Results: Results showed that 14 mm tongue displacement during "at," with velocities of 54mm/s and 52mm/s. Velum contact occurred in 78% of total frames from 17500 frames.

Impact: These results provide insights into tongue and velum movement during speech, potentially aiding clinicians in diagnosing speech disorders and improving therapeutic techniques. This study also suggests a question on the neural control of articulation and speech production accuracy.

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Keywords