Speech synthesis technology is becoming more mature. In order to improve the quality of synthetic emotional speech， this study proposes a method combining end-to-end emotional speech synthesis with prosodic correction. Based on the Tacotron model， the prosodic parameters are modified to improve the emotion expression power of the synthetic system. Tacotron model is first trained with a large neutral corpus， and then a small emotional corpus is used to train and synthesize emotional speech. Then the Praat acoustic analysis tool is used to analyze the prosodic features of emotional speech in the corpus and summarize the parameters of different emotional states. Finally， with the help of this rule， the fundamental frequency， duration and energy of the corresponding emotional speech synthesized by Tacotron are modified to make the emotional expression more accurate. The results of objective emotion recognition experiment and subjective evaluation show that this method can synthesize more natural and expressive emotional speech.