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pISSN : 2233-9221 / eISSN : 2713-8720

2020 KCI Impact Factor : 0.08
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2021, Vol.11, No.1

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  • 1.

    How the food names in A Dream of Red Mansions translated into Korean

    JINTIANXIANG | 2021, 11(1) | pp.7~34 | number of Cited : 0
    Abstract PDF
    Machine translation powered by artificial intelligence is now beingwidely used for such areas as legal translation, which require high-levelprofessional knowledge and skills and thus were used to be considered exclusivelyfor human translators. The Korea Legislation Research Institute, which hastranslated the statutes of the Republic of Korea for 30 years, has begun to usemachine translation. Yet there are issues to be addressed, including legal problemsassociated with using machine translation. If we could come up with a propersolution to these issues based on in-depth research, machine translation would betterassist human translators. (Korea Legislation Research Institute, Korea)
  • 2.

    Practices and challenges in translating statutes using machine translation

    Lee, Sang-Mo | 2021, 11(1) | pp.35~56 | number of Cited : 0
    Abstract PDF
    Machine translation powered by artificial intelligence is now beingwidely used for such areas as legal translation, which require high-levelprofessional knowledge and skills and thus were used to be considered exclusivelyfor human translators. The Korea Legislation Research Institute, which hastranslated the statutes of the Republic of Korea for 30 years, has begun to usemachine translation. Yet there are issues to be addressed, including legal problemsassociated with using machine translation. If we could come up with a propersolution to these issues based on in-depth research, machine translation would betterassist human translators. (Korea Legislation Research Institute, Korea)
  • 3.

    Problems in non-native speakers' communication in legal sttings: Two cases of U.S. police interviews with suspects

    Jieun Lee | 2021, 11(1) | pp.57~86 | number of Cited : 0
    Abstract PDF
    This paper examinescommunication problems or miscommunication in legal settings. When theparticipants in the communicative interaction do not share similar linguistic andcultural backgrounds, they are more likely to create misunderstanding or developmiscommunication. Non-native speakers with limited linguistic resources arerestricted from fully participating in legal communication, where understanding andclarity is vital. Their linguistic disfluency and deviations from the so-called standardEnglish may cause serious misunderstanding that have legal ramifications. Based ona discourse analysis of video-recorded US police interviews, this paper examinesmiscommunication during the investigative interviews with suspects from Koreanspeaking backgrounds, which involved two non-professional interpreters. While bothof them were Korean-American police offciers, they differed in terms of the extentof the provision of interpreting. In one case, the interpreter played a very minimalrole as an interpreter during the interview, while the suspect largely managedcommunication in English on his own, and this contributed to the lack of certaintyover his confession to the crime and eventually led to his acquittal. In the othercase, the interpreter interpreted throughout the investigative interview of the suspectbut her interpreting added to the complexity of the communication problem, mainlydue to her lack of interpreting skills. It is argued that given that a greater
  • 4.

    Machine translation of detective novels: A case study of Conan Doyle's works

    Heakyung Im | 2021, 11(1) | pp.87~115 | number of Cited : 0
    Abstract PDF
    This article delves into the types of errors found in theproducts of machine translation in comparison with those of human translators. Thefocus of comparison is placed on the translation of specific contextual informationthat reflects the social, political, and ideological aspects of the original text. Thisinformation should be taken into consideration by both human and machinetranslators engaged in Korean-English translation, especially in the case of detectivenovels. This article is aimed at studying the difference between human translatorsand machine translators when translating contextual situations. In this regard,analysis will be conducted based on the typologies of machine translation errorssuggested by Seo Bo-Hyun and Kim Soonyoung. In order to discover any potentialdifference between human translators and machine translators, this article comparesthe texts translated by humans and machine translators. Currently, literarytranslation, such as the specific genre of detective novels, is unlikely to be subjectedto automated translation that provides text translation based on computer algorithmwithout human involvement. However, there is a possibility that automatedtranslation of texts like detective novels will be more common in the future if thereis a huge amount of training data available including specific contextual informationand highly sophisticated algorithm can be designed by computer scientists. The aim of this study is to analyze the types of errors in the machine translation ofdetective novels. It was revealed that the error types found in English-Koreanmachine translation of detective novels were limited because of the small size of thedata. (Dongguk University Seoul, Korea)