We have developed a system that recognizes the facial expressions in Taiwanese Sign Language (TSL) using a phoneme-based strategy. A facial expression is decomposed into three facial phonemes of eyebrow, eye, and mouth. A fast method is proposed for locating facial phonemes. The shapes of the phonemes were then matched by the deformable template method, giving feature points representing the corresponding phonemes. The trajectories of the feature points were tracked along the video image sequence and combined to recognize the type of facial expression. The tracking techniques and the feature points have been tailored for facial features in TSL. For example, the template matching methods have been simplified for tracking eyebrows and eyes. The mouth was tracked using the optical flow method, taking lips as homogeneous patches. The experiment has been conducted on 70 image sequences covering seven facial expressions. The average recognition rate is 83.3%.