[Abstract] In recent years, the combination of particle swarm optimization algorithm and neural network can effectively improve the global search for the best, but also improve the speed of convergence. Combines particle swarm optimization algorithm and the neural network is applied in English teaching, through the extraction of training students' translation samples, with the trained neural network model of particle swarm optimization to correct the students' ability of English translation level of analysis, help teachers to estimate the students' translation ability level, provide reference for the next step of teaching. Starting from the mathematical model of particle swarm optimization algorithm and the basic principle of algorithm flow and artificial neural network model, the learning ability analysis model is proposed to determine the topological structure of neural network and the node number of hidden layer. The results of the case study show that the model can improve the quality of English translation teaching.