| The globe has seen tremendous progress in the development of computer science and technology.As a result of this situation,humans have gained more abilities in the use of big data,which has changed the language service business.The urbanization of computer science has resulted in a proliferation of online translation platforms and apps,which account for a sizable portion of the current translation business.Automation in translation is a developing trend,resulting in the modes of Computer-Aided Translation(CAT),Machine Translation(MT),and Post-editing(PE).The MT+PE mode is becoming more popular in translation projects since it not only increases productivity by reducing working hours but also enhances output quality for language service providers,translators,and post-editors.This thesis depicts a translation effort using the MT+PE method and it uses an excerpt from Julia Millet’s book A Children’s Bible as its original text.This paper includes research on the most prevalent MT error types observed in the project,as well as associated PE strategies,by examining the project’s MT and PE outputs.The top five most prevalent types of errors in the project’s MT output,according to the data,are incorrect word meaning,word order,lack of cohesiveness,poor rhetoric translation,and sentence integration.The author proposes post-editing procedures for machine translation of the book based on the data obtained in this project: pick the right term meaning,use your professional background knowledge and rearrange the misuse of coherent devices to make its logical meaning clear and correct the mistake in terms of coherence.Using the statistical results from the first two chapters of A children’s Bible as a model,this thesis summarizes the basic characteristics of the error types in machine translation of the excerpt,and then suggests post-editing strategies for future book translation of similar kind. |
