4pSCa10. Using principal component analysis of tongue surface shapes to distinguish among vowels and speakers.

Session: Thursday Afternoon, June 19

Author: Maureen Stone
Location: Univ. of Maryland, School of Medicine, Div. of Otolaryngol.--HNS, Frenkil Bldg., Ste. 500, 16 S. Eutaw St., Baltimore, MD 21201
Author: Y. Cheng
Location: Univ. of Maryland, College Park, MD 20742
Author: A. Lundberg
Location: Johns Hopkins Univ., Baltimore, MD 21218


The present study uses principal component analysis (PCA) to examine sagittal tongue contours for five English vowels taken from ultrasound images. The vowels are repeated three to five times each in a /pVp/ carrier utterance. Of particular interest is the use of plots of the coefficients of the eigenvectors to distinguish both subjects and vowels, and the building of a linear model to fit their family of data. Data will be transformed to normalize surface length across contours. Short contours will be stretched in the x direction to the length of the longest curve. The x and y dimensions will be stretched equally for each curve to preserve scale. Preliminary data indicate fairly good success distinguishing among three subjects and four vowels using a linear model based on the first few components. Methods of improving this result are being explored using factor analysis or optimal fitting. XXSU SC

ASA 133rd meeting - Penn State, June 1997