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PARAFAC Analysis of 3-D Tongue Shape

PARAFAC Analysis of 3-D Tongue Shape. Yanli Zheng, Mark Hasegawa-Johnson ECE Department University of Illinois at Urbana-Champaign. Part I. Background. WHY is the factor analysis of tongue shape meaningful ? Speech Motor System. Anatomical View Basic Vowel Diagram.

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PARAFAC Analysis of 3-D Tongue Shape

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  1. PARAFAC Analysis of 3-D Tongue Shape Yanli Zheng, Mark Hasegawa-Johnson ECE Department University of Illinois at Urbana-Champaign

  2. Part I. Background WHY is the factor analysis of tongue shape meaningful? • Speech Motor System

  3. Anatomical View Basic Vowel Diagram Part I. Background (cont. Why?) 2. Representing Vowel • Frequency Domain

  4. X-ray images Part I. Background HOW to analysis the vowels in the context of anatomy? 2-D PARAFAC analysis by Richard Harshman(1977) Measuring Scheme

  5. Results:Two Factors account for 92% variance. Background (cont. Results of Harshman) Vowels Loading Grids Factors

  6. Part I. BackgroundWhy is 3D Different from 2D? • Linear Source-Filter Theory: • Vowel Quality is Determined by Areas • Area Correlated w/Midsagittal Width • Distinguish important in Speech Synthesis • Clinic Application

  7. Part II. Algorithms Introduction • PARAFAC (Parallel Factor Analysis) xijk: tongue shape measurement for ith data point, jth vowel and kth speaker. aif: fth factor contribution to ith data point bjf: loading of phoneme j on fth factor ckf: loading of speaker k on fth facotor

  8. Part II. Algorithms Introduction 2. Tucker3 Model(used in the validation of PARAFAC model)

  9. Part III. 3-D Factor Analysis of MRI-Derived Tongue Shapes • Subjects: 5 subjects successfully imaged (three male speaker: m1,m2, m3; and two female speaker: f1,f2). • MRI Image Collection • T1-weighted • GE Signa 1.5T • 3mm slices • 24 cm FOV • 256 x 256 pixels • Coronal, Axial • 11-18 Sounds • per Subject. • Breath-hold in • vowel position • for 25 seconds

  10. Part III. 3-D Factor Analysis of MRI-Derived Tongue Shapes3. Image Viewing and Segmentation: the CTMRedit GUI and toolbox • Display series of CT or MR image slices • Segment ROI manually or automatically • Interpolate and reconstruct ROI in 3D space

  11. 3D-Tongue Shape 2) How to define the measuring grid? Part III. 3-D Factor Analysis of MRI-Derived Tongue Shapes4. PARAFAC Analysis

  12. Part III. 3-D Factor Analysis of MRI-Derived Tongue Shapes4. PARAFAC Analysis(cont.)3) Result: 2 Factors are extracted, with 83.8729 % variance explained

  13. Part III. 3-D Factor Analysis of MRI-Derived Tongue Shapes4)Validation of the Result • Split-half test (example for f1,f2 and m3) Correlation Coefficients Grid Contribution 0.9646 Vowel Loading 0.9279

  14. 4)Validation of the Result b) Check the reliability of the solution • Try different start points, check whether all the solutions converge to the same solution. c) Core Consistency Testing (by Rasmus Bro,1998)

  15. Degenerated result for 3-factor PARAFAC Model Correlation Coefficients 1&2 2&3 1&3 Grid Contribution -0.5362 0.9632 -0.6045

  16. Part IV. Conclusion • 3-D PARAFAC Analysis of Tongue Shape suggests the “Hierarchical Control” • This research and the follow-up expected research in the MR Microscopy, and Dynamic Imaging aim to : 1. Provide new anatomical information to speech scientists and speech pathologists 2. Lay the foundation for future research with disordered populations.

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