On The Application Of Chinese-English Machine Translation To Business Texts

This is a study of the application of Chinese-English machine translation to the translation of business texts. It makes an in-depth comparative study of the rule-based machine translation system and statistics-based machine translation system, as represented by Google Translate and Systran Translation respectively, and finds some major problems in machine translation for business texts, and accordingly, puts forward some suggestions for improvement.Beginning with a brief review of the development of research on machine translation at home and abroad, this paper then discusses the text type of business texts, their classification and features, as well as the feasibility and practicality of translating business texts with a machine translation system. Then it compares and analyzes two business text translations produced by Systran and Google systems at both lexical and syntactic levels from the perspectives of comprehensibility and fidelity in accordance with the evaluation criteria proposed by Makoto Nagao. Finally, a number of feasible suggestions are put forward, including a hybrid approach and a preference-based WSD approach to the translation of the words "JIANG" and "YIN" in business contexts in the hope of improving the quality of machine translation for business texts.Due to the subjective and objective restrictions, there are inevitably some limitations in this paper, such as the limited length of the selected samples that seem to be not enough for theoretical generalizations, which are calling for further research.