Automatic phrasing is essential to Mandarin textto-speech synthesis. We select word format as target linguistic feature and propose an HMMbased approach to this issue. Then we define four states of prosodic positions for each word when employing a discrete hidden Markov model. The approach achieves high accuracy of roughly 82%, which is very close to that from manual labeling. Our experimental results also demonstrate that this approach has advantages over those part-ofspeech-based ones.
