Tongue motion averaging from contour sequences.

In this paper, a method to get the best representation of a speech motion from several repetitions is presented. Each repetition is a representation of the same speech captured at different times by sequence of ultrasound images and is composed of a set of 2D spatio-temporal contours. These 2D contours in different repetitions are time aligned first by a shape based Dynamic Programming (DP) method. The best representation of the speech motion is then obtained by averaging the time aligned contours from different repetitions. Procrustes analysis is used to measure the contour similarity in the time alignment process and to get the averaged best representation. To get the point correspondence for Procrustes analysis, a nonrigid point correspondence recovery method based on a local stretching model and a global constraint is developed. Synthetic validations and experiments on real tongue motion are also presented in this paper.