Prosodic prediction plays an important role in text-to-speech system, it is a prerequisite for the generation of prosodic parameters, such as silence, fundamental frequency and duration, and its accuracy to a large extent determines both the naturalness and intelligibility of synthesized voice. In prosodic phrase prediction, this paper first analyses the relationship between syntactic features and each prosodic phrase units at first. Then we evaluate the effects of syntactic features in experiment. The experiment results show that the the proformance of prosodic phrase prediction model is improved by adding syntactic features into the features set. We also try to improve the prosodic phrase prediction model using new feature sets based on experience learned from former experiments. In stress prediction, this paper focus on prediction stress in discourse not only sentence. A statistical method designed to calculate the informativeness of word is proposed. The experiment results show the proformance of stress prediction model is improved by discourse features including word informativeness. In detail, the main work of this dissertation includes the following: 1）Investigate how to use syntactic features to improve the performance of prosodic phrase prediction model. First we analyses the corpus and find that the relationship between low level prosodic phrase and low level syntactic phrase structure is close. Meanwhile, the same phenomenon exists between high level prosodic phrase and high level dependency structure. The experimental results show that prediction models of prosodic word and prosodic phrase achieve the best performance with syntactic phrase and dependency features, while the models with dependency features outperform other models when predicting intonational phrase. 2）Evaluate the relationship between different level prosodic pharse untis and corresponding level syntactic features. We classify the features into global and local features sets. The experimental results show the performance of prosodic word and prosodic phrase prediction with local features in addition to the baseline features outperform other features combination. Meanwhile, the best result of the intonational phrase prediction is achieved when syntactic global features and baseline features are selected. The results show that the higher prosodic phrase boundaries prediction dependent on higher level syntactic features. 3）First we evulate the effect of sentence level feat...
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