Research on Chinese-English Patent Machine Translation Based on Fusion Strategy Model

Abstract

In order to improve the translation quality of the machine translation model in the field of patent text, this paper proposes a patent knowledge fusion strategy. On the one hand, it integrates the structural knowledge, special phrases and professional terms in the patent text into the translation model as embedded comments, so as to improve its translation effect. On the other hand, based on XLNet, the basic translation model of Transformer is improved, and the translation performance of the model is further improved on the basis of integrating professional knowledge. The simulation results show that compared with the basic Transformer model and the Transformer model that only introduces fusion strategy, BLEU values of the proposed machine translation model combining fusion strategy and improved Transformer for the Chinese-English and English-Chinese translation tasks has increased by 3.77, 1.79, and 2.17, 0.46, respectively. It has a significant improvement in improving the quality of patent literature translation and is worthy of further research and promotion.