Figure 1.
A schematic illustration of the analysis procedure.
Figure 2.
An illustration of modeling with Locally-Weighted Regression (LWR).
For a particular point (black cross) a local region is defined in articulator space by a Gaussian-shaped kernel (gray dashed curve). A line is fit in the local region using a weighted least-squares solution, indicated by the black dashed line. The global fit is generated by repeating this procedure at a large number of local regions. The resulting fit can be quite complex (gray curve), and depends on the width of the kernel.
Figure 3.
Planar robot arm configurations corresponding to the top eight (a) highest and (b) lowest average Jacobian values.
Figure 4.
(a) Cross-distances in more detail (lip aperture (LA), velic aperture (VEL), and constrictions of the tongue tip (TTCD), tongue dorsum (TDCD) and tongue root (TRCD). (b) Articulatory posture variables – jaw angle (JA), tongue centroid (TC) and length (TL), and upper and lower lip centroids (ULC and LLC).
Figure 5.
Histograms of the sum-squared values of Jacobians computed for different consonants on speaker Eng5's data.
Table 1.
Medians of sum-squared values of the Jacobians tabulated by category and speaker (left).