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Application of Corpus Analysis Software and Error Analysis Theory on Non-English Majors’ Chinese-English Translation Features

Author(s)

Can Shu

Affiliation(s)

School of Foreign Language, Wuhan Business University, Dongfeng Boulevard, Wuhan, China

Abstract

This research focuses on non-English major students’ Chinese-English (C-E) translation features. It aims at annotating and summarizing the features and error types in students’ C-E translation by applying to corpus analysis software Readability Analyzer. This study first collects students’ C-E translation texts from a computer-based exam, then forms a self-constructed corpus and a reference corpus. The translation materials in the target corpus and the reference corpus are first analyzed and compared by Readability Analyzer to figure out the features of students C-E translation texts from the perspectives of sentence length, word length, percentage of difficult words, Flesch Reading Ease, Dale-Chall Score, Fry Readability Grade Level. After that, different types of errors in students C-E translation are labeled and analyzed based on statistical analysis and Error Analysis (EA) theory. According to Readability Analyzer, students C-E translation texts have the following features. From passage statistics, it shows that translation texts that get lower scores tend to use shorter sentences and easier words. In addition, from readability scores, Flesch scores, Dale-Chall Scores shows and Fry Readability Grade Level are taken into consideration. Flesch scores shows that compared with the reference corpus, students’ translation which get lower scores are harder to understand since there are more language errors than higher-score translation. Dale-Chall Scores indicate that translation materials which score 8-9 are very close in the difficulty of word-using with the reference corpus. Fry Readability Grade Level shows that texts of lower scores are simpler and more accurate than texts of higher scores. According to Error Analysis (EA) Theory, students’ errors are further classified and discussed on lexical level, sentence level and textual level. The conclusions of this research are expected to make contributions to the improvement of C-E translation teaching and help college students, especially non-English majors, to enhance their C-E translation competence.

Keywords

Chinese-English translation; corpus analysis; Error Analysis Theory

References

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