关键词: 韵律结构预测, 语法结构, 韵律短语, 语法树高度, 错误驱动的规则学习算法（TBL）

Abstract: Predicting precise prosodic structure is one of the most important aspects for improving the naturalness of synthesized speech in text to speech synthesis.10000 sentences with part-of-speech tags are used for manually labeling prosodic word and prosodic phrase under a linguistic expert’s guidance.A new feature based on the height of syntax tree is proposed in the paper for describing the degree of closeness between the adjacent lexicon words according to the hierarchal syntax structure.Analysis on the relationships between height of syntax tree and prosodic phrase boundary shows that the height of syntax tree，part-of-speech and length of lexicon word are the three most important features for prosodic phrase boundary prediction.Therefore these three features are employed to train a TBL based model with 400 training sentences.Experiments demonstrate that the approach achieves 75.2% of precision，77.1% of recall and 76.1% of F-Score.

Key words: prosodic structure prediction, syntax structure, prosodic phrase, height of syntax tree, Transformation-based Error-driven Learning（TBL）