Exploring a canonical correlation analysis technique for the study of articulatory coordination.
Sungbok Lee, Dani Byrd · The Journal of the Acoustical Society of America · 2010
Canonical correlation analysis provides an effective way to visualize the patterns of association or inter-relations between two sets of variables. When observations or measurements are curves such as time series or serial data in general, a canonical correlation analysis technique provided by the functional data analysis (FDA) methodology [Ramsay and Silverman (2005)] is an ideal choice. Although the FDA canonical correlation analysis has a potential usefulness in the study of articulatory coordination, it has been rarely utilized for that purpose. In this study, the FDA canonical correlation analysis technique is applied to midsagittal vocal tract contour data produced in four different emotions (neutral, anger, happiness, and sadness) obtained by a real-time magnetic resonance imaging technique. The purpose is to examine overall differences in the coordination of x and y components of vocal tract contours as a function of emotion. Results indicate that differences in the variance-covariance matrices of x and y components as well as differences in the first three canonical variates among the four emotions are clearly observable, which indicates different weighting patterns of x and y components along the vocal tract for emotional contrast. Those results and other possible applications of the technique will be discussed. [Work supported by NIH.]