Application of Computer Technology in Translation Teaching

Abstract

The form of English passive structure has a significant influence on its Chinese translation. Based on the self-built BTI corpus, this paper selects the previous data on the standard translation characteristics of English passive structure based on big data statistics as the reference, uses the method of variable analysis, and investigates ten Chinese versions of marked passive structures in students' English translations from the perspective of comparative statistics. Data comparison shows a significant difference between the translation features shown in the BTI corpus and the standard translation features reflected in the reference data. Compared with the reference data, the proportion of long and short passives translated into active and agent theme structures decreased significantly. After receiving the theoretical explanation and training of translation skills, students pursue applying various translation skills on purpose while ignoring the most common and basic translation skills. For another, the deviation between the translation form features in the BTI corpus and the translation standard features reflected by the reference data shows the decline in the quality of students' translation. The results help teach reflection and enlightenment to translation teaching with the aid of computer technology in the future.