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Ultrasound (US) imaging is an excellent means of observing tongue motion during speech. Tracking the tongue contour in US video is required for analysis of this motion, but most currently available techniques suffer from either a lack of temporal consistency or a lack of robustness to difficult conditions such as a rapidly deforming tongue or momentarily poor image quality. This paper proposes a new algorithm combining active contours, active shape models and particle filtering that addresses these shortcomings. The strength of this approach lies in the fact that it maintains multiple tongue shape hypotheses simultaneously. Experimental results show that this approach outperforms a classic active contour algorithm as well as a shape-constrained variant thereof, particularly in difficult tracking conditions.