Analysis on the Recent Trends in Machine Translation

Abstract

Machine translation is to translate one language into another language, which has undergone a great evolution. The model of machine translation has been continuously improved, aiming to make the translation effect closer to the artificial translation. This article briefly summarizes the development history of machine translation, and introduces the main models of each stage of development. The initial machine translation mode is the Rule Based Machine Translation (RBMT) and Statistical Machine Translation (SMT). Recent mainstream translation approach enables Neural Machine Translation (NMT). It includes the input and the output, attention mechanism, and BLEU evaluation method. On this basis, there are also many expansion and innovation models, such as GPKD and other models to improve the evaluation effect. In general, machine translation can replace a part of human translation. However, it cannot completely replace human beings, because of the different human thinking and machine logic. People and machines have to cooperate with each other to improve the common efficiency.