Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing
Machine translation (MT) systems such as Google Translate, Bing or Youdao are increasingly present in everyday life. Anecdotal evidence suggests that language students might use them to produce written work in the target language (TL) and thus possibly get around a potentially difficult writing task...
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| Format: | Article |
| Language: | English |
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Cranmore Publishing
2021-06-01
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| Series: | International Journal of TESOL Studies |
| Subjects: | |
| Online Access: | https://www.tesolunion.org/attachments/files/FZJNKANDGZAMTG4FNDLMBMTDHFY2I36NDRI3ZGJJAOTVJ9OTDKFZDRI3NGM5DZJA46NZYWEYTNK9YTYW7YZGZBYTKX8LJE3CMZG3AOTI0ALJE3.pdf |
| _version_ | 1819282324415578112 |
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| author | Zhenyan Ye |
| author_facet | Zhenyan Ye |
| author_sort | Zhenyan Ye |
| collection | DOAJ |
| description | Machine translation (MT) systems such as Google Translate, Bing or Youdao are increasingly present in everyday life. Anecdotal evidence suggests that language students might use them to produce written work in the target language (TL) and thus possibly get around a potentially difficult writing task. The crucial question to ask would be whether it is possible to differentiate the output of MT from learner language. This paper seeks to address this question by comparing the lexical features of these two types of discourse in the Chinese context. In particular, it examines the use of English translation equivalents of polysemous Chinese words in two parallel corpora: A Chinese webpage corpus translated into English using Bing and Youdao on the one hand and a Chinese learner writing corpus on the other. While the comparison yields similar error rates, it also establishes that human learners and translation engines have difficulties with different sets of words. Word frequency also plays a significant role in differentiating between the two sets of output. The paper concludes with the finding that MT output is sufficiently different from learner language in terms of lexis. The findings could be used to create an algorithm for the detection of ethics code violation through the use of MT engines in written assignments. |
| first_indexed | 2024-12-24T01:13:47Z |
| format | Article |
| id | doaj.art-6a8a4f8c813447b98ae64d6e058b1b08 |
| institution | Directory Open Access Journal |
| issn | 2632-6779 2633-6898 |
| language | English |
| last_indexed | 2024-12-24T01:13:47Z |
| publishDate | 2021-06-01 |
| publisher | Cranmore Publishing |
| record_format | Article |
| series | International Journal of TESOL Studies |
| spelling | doaj.art-6a8a4f8c813447b98ae64d6e058b1b082022-12-21T17:22:49ZengCranmore PublishingInternational Journal of TESOL Studies2632-67792633-68982021-06-01328810410.46451/ijts.2021.06.07Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English WritingZhenyan Ye0University of Hong Kong, ChinaMachine translation (MT) systems such as Google Translate, Bing or Youdao are increasingly present in everyday life. Anecdotal evidence suggests that language students might use them to produce written work in the target language (TL) and thus possibly get around a potentially difficult writing task. The crucial question to ask would be whether it is possible to differentiate the output of MT from learner language. This paper seeks to address this question by comparing the lexical features of these two types of discourse in the Chinese context. In particular, it examines the use of English translation equivalents of polysemous Chinese words in two parallel corpora: A Chinese webpage corpus translated into English using Bing and Youdao on the one hand and a Chinese learner writing corpus on the other. While the comparison yields similar error rates, it also establishes that human learners and translation engines have difficulties with different sets of words. Word frequency also plays a significant role in differentiating between the two sets of output. The paper concludes with the finding that MT output is sufficiently different from learner language in terms of lexis. The findings could be used to create an algorithm for the detection of ethics code violation through the use of MT engines in written assignments.https://www.tesolunion.org/attachments/files/FZJNKANDGZAMTG4FNDLMBMTDHFY2I36NDRI3ZGJJAOTVJ9OTDKFZDRI3NGM5DZJA46NZYWEYTNK9YTYW7YZGZBYTKX8LJE3CMZG3AOTI0ALJE3.pdflexical transferpolysemymachine translationwriting |
| spellingShingle | Zhenyan Ye Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing International Journal of TESOL Studies lexical transfer polysemy machine translation writing |
| title | Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing |
| title_full | Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing |
| title_fullStr | Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing |
| title_full_unstemmed | Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing |
| title_short | Polyseme Transfer in the Chinese to English Machine Translation Output and Chinese Students' English Writing |
| title_sort | polyseme transfer in the chinese to english machine translation output and chinese students english writing |
| topic | lexical transfer polysemy machine translation writing |
| url | https://www.tesolunion.org/attachments/files/FZJNKANDGZAMTG4FNDLMBMTDHFY2I36NDRI3ZGJJAOTVJ9OTDKFZDRI3NGM5DZJA46NZYWEYTNK9YTYW7YZGZBYTKX8LJE3CMZG3AOTI0ALJE3.pdf |
| work_keys_str_mv | AT zhenyanye polysemetransferinthechinesetoenglishmachinetranslationoutputandchinesestudentsenglishwriting |