Research on English translation technology based on machine learning

Abstract

In the era of economic globalization, translation tasks between different languages are becoming more and more frequent, especially English as the most widely used language. The development of information technology has promoted the development of machine translation. Machine translation is faster than human translation. But machine translation also has certain quality problems. So far, machine translation still has problems such as missing translation and poor text translation. In order to solve the current problems, this paper conducts in-depth research on the English translation technology based on machine learning. First, this paper analyzes the principle of machine translation and the Transformer model. In order to improve the quality of machine-translated translations, improvements are proposed to current translation models. This improvement is to optimize the normalization layer of the Transformer model. Based on this improvement, an English translation system based on machine learning is designed. After experimental verification, the improved translation model in this paper can improve the accuracy of translation.