Automatic tongue contour tracking in ultrasound sequences without manual initialization

Tracking the movement of the tongue is important for understanding how tongue shape change contributes to speech production and control. Ultrasound imaging is widely used to record real time information on the tongue surface; however, noise, artefacts, and the presence of spurious edges render automatic detection of tongue contours without manual initialization difficult. In this paper, we propose a method to extract ultrasound tongue surface contour in a totally automatic way using a three-step procedure: 1) noise reduction using a non-local mean filter; 2) use of a quadratic function to roughly fit the surface contour based on points obtained with a Robert cross operator; and 3) an automatic refinement based on gradient shift and relative distance of candidate points to the initial rough contour point. Experiments are conducted on isolated vowels and on a continuous utterance of vowel sequence. The Mean Sum of Distances criterion shows that the proposed method provides results on a par with the popular EdgeTrak algorithm on these two data sets, as compared to hand-scanned contours, but without any manual initialization.