Automatic Phrase Breaks Prediction in Chinese Sentences
Zuoying Wang · Zhongwen xinxi xuebao · 2003
In TTS system, it is very important to mark phrase breaks correctly for high naturalness and quality of output speech. The paper discusses an algorithm for automatically predicting phrase breaks in Chinese sentences. At first, the text is segmented to words and converted to a sequence of part-of-speech tags; then based on the POS tags sequence parameters and phrase-break distance information from training, Markov model is used to get the most likely phrase break sequence. In this paper several model parameters and rules are used, the recalling rate of predicated breaks is 68.2%, the overall predicted juncture correct rate is 85.1%.