The purpose of this thesis is to improve the break tags prediction which is generated form acoustic feature and linguistic feature for Mandarin speech synthesis. However there are no acoustic features in TTS synthesis system, linguistic features extracted from context data are the only imformation. This research utilize different Artitficial Neural Network model to predict break tags. In order to improve the break prediction, more linguistic feature descrbing for syntactic information are added. Furthemore, we predict pause duration based on Neural Network. The experiment result showed that partial imformation of syntax tree can improve break prediction actually, and the performance of the pause prediction is also improved.