Design of Automatic Translation System for English for Special Purpose in Agriculture Based on Neural Machine Translation
Meilin Wang · 2023
Agricultural terms have some unique characteristics, which make them need special treatment in machine translation. Agriculture is a highly specialized field, with a large number of specialized terms and concepts, which are not common in general texts. Neural Machine Translation (NMT) technology has made remarkable progress in recent years, and has been successful in various fields. The purpose of this thesis is to design and develop an automatic English translation system for special purposes in agricultural field based on NMT, so as to meet the translation needs of professional knowledge in agricultural field. Based on the embedded environment, the system software is designed. By using the sample training mechanism of deep learning algorithm and combining the characteristics of agricultural terminology translation, the system interaction and translation data are trained separately. By redesigning the interaction hardware, the hardware structure of the translation system is completely defined. The practical application test results with the comparison system show that the translation system designed by the deep learning algorithm has the characteristics of high efficiency, high translation accuracy and good stability in the interactive translation of agricultural terms.