국내학부 번역전공자의 구글 기계번역 포스트에디팅 과정(process) 및 행위 연구
Process research into post-editing: How do undergraduate students post-edit the output of Google Translate?
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In his research on machine translation post-editing (Lee 2017; Lee 2018), the author revealed two important factors: (1) types of post-editing errors made by five undergraduate students majoring in English-Korean translation and (2) the students’ perceptions of post-editing of free online machine translation (FOMT). As a follow-up study to Lee (2017, 2018), this paper aims to show how undergraduate students post-edit the output of Google Translate and to discuss implications of findings for post-editor training. For this purpose, the author conducted a small-scale experiment, in which the five students post-edited medical texts with Google Translate, while verbalising their thoughts at the same time. Data were collected by recording the students’ think-alouds and computer screen activities. Analysis shows that the students inefficiently performed post-editing by using dictionaries too frequently and spending too much time on non-technical words. In addition, some students pre-edited the source text in a questionable way and translated the source text from scratch for unjustifiable reasons. Based on these results, the study discusses four issues that should be addressed to improve post-editor training. First, the top priority should be given to improving students’ basic translation competence rather than skills specific to post-editing. Second, instrumental subcompetence is still of critical importance to developing students’ post-editing competence. Third, revision should be adopted as a main component of translator/post-editor training. Fourth, research on language-specific pre-editing should be conducted before integrating pre-editing into post-editor training programmes.
Abstract
In his research on machine translation post-editing (Lee 2017; Lee 2018), the author revealed two important factors: (1) types of post-editing errors made by five undergraduate students majoring in English-Korean translation and (2) the students’ perceptions of post-editing of free online machine translation (FOMT). As a follow-up study to Lee (2017, 2018), this paper aims to show how undergraduate students post-edit the output of Google Translate and to discuss implications of findings for post-editor training. For this purpose, the author conducted a small-scale experiment, in which the five students post-edited medical texts with Google Translate, while verbalising their thoughts at the same time. Data were collected by recording the students’ think-alouds and computer screen activities. Analysis shows that the students inefficiently performed post-editing by using dictionaries too frequently and spending too much time on non-technical words. In addition, some students pre-edited the source text in a questionable way and translated the source text from scratch for unjustifiable reasons. Based on these results, the study discusses four issues that should be addressed to improve post-editor training. First, the top priority should be given to improving students’ basic translation competence rather than skills specific to post-editing. Second, instrumental subcompetence is still of critical importance to developing students’ post-editing competence. Third, revision should be adopted as a main component of translator/post-editor training. Fourth, research on language-specific pre-editing should be conducted before integrating pre-editing into post-editor training programmes.
참고문헌 (33)
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