원문정보
초록
영어
Artificial neural network based machine translations have become common since 2016 and the advancements in quality of said translations call for a change in the translation and interpretation education sector. It is true that some machine translations are comprehensible to a certain degree, but they also tend to translate texts into something that is very different from the original. Therefore, they cannot be said to have reached a reliable level. However, considering the speed at which the quality of machine translation is being improved, there is a need to learn about it in translation classes. Machine translations require human post-editing. Therefore, it is necessary to train students to become familiar with the task of post-editing and to offer them some guidelines with which to manage said task with speed. This study attempts to draw such guidelines using Korean press articles as data. Press articles cover various current topics related to politics, economics, social issues, cultural issues and others. They also contain reports, columns and editorials on different subjects and genres in various different forms of texts, such as headline texts and main texts, which are very useful in practicing translation in class. The practice of translation using press articles can help students set a strong foundation for developing the capacity to manage diverse forms of text. This study uses Google Translation, and Naver search engine's PAPAGO. The study uses as reference the results of a preceding research(Park, 2018) on post-editing class training and student reaction. According to said case study, students felt heavily burdened when they had to post-edit machine translations. There were also students that wondered about the range and extent in which they could modify the translations. In this study, time was limited, as real life post-editing requests from clients tend to be time-pressing. Also, limited to news article texts, a corpus was created according to article content and errors were analyzed applying the machine translation editing code(Lee, 2018) to develop post-editing guidelines. News article translations were divided into three groups for the purpose of comparing results and quality: human translations, post-edited machine translations that were done without any guideline, and post-edited machine translations that followed the developed guidelines. Afterwards, translators of each group were interviewed in-depth to assess the suitability of implementing said guidelines. There are no post-editing guidelines for machine translations as of yet as machine translation is still in its early, developing stages. However, this study is significant in that it proposes a set of guidelines for post-editing Korean-Japanese and Japanese- Korean machine translations under the assumption that the role of human translators will extend to co-working with machine translations as the use of these translations becomes more and more common. The guidelines should be implemented in translation teaching courses. These will need to be modified along with advancements and changes in machine translation. They need to be continuously evaluated and adjusted for the purpose of training effective, fast working post-editing professionals.