The basic theory of the neural network model used in this research is particle swarm optimization, applied to English-Chinese translation retrieval and model optimization. The decoded form obtains the translation task sequence. This topic uses TensorFlow to complete the construction of the translation system. This research solves the typical lack of semantic information in the hierarchical model. The demonstration of examples shows that the neural network model based on particle swarm optimization can significantly improve the quality of machine translation.