English Translation Model Based on Intelligent Recognition

With the advancement of science and technology, many types of jobs that used to rely solely on manpower have been impacted, but in turn, many jobs have benefited from the development of science and technology, and with the help of technology, both efficiency and effect have been improved. During the experiment, this paper designs two groups of experiments, the first group is the baseline model Transformer, and the second group is the improved model proposed in this paper, which is verified by comparing the BLEU score values of the two models on the same dataset. The results show that the final score of the improved model proposed in this paper is higher than that of the original baseline model, and the Transformer model after adding the part-of-speech information vector improves the BLEU value by 0.54 points. Experiments show that the improvement of the model is effective.