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      한국어 번역을 위한 문화소의 기계번역 연구-중국 외교연설문 번역의 정확도 평가를 중심으로- = Study of Cultural Vocabulary in Machine Translation for Korean Translation -Focusing on the accuracy evaluation of Chinese diplomatic speech translation-

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      https://www.riss.kr/link?id=A105966799

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      The development of translation machines represented by machine translation and AI translation has recently become a hot topic in the society. Particularly, in recent years, the accuracy and fluency of translation machines have been greatly improved thanks to the use of neural network technology (NMT,Neural Machine Translation), and translation machines have become the main focus of public attention.
      In addition, the translation machine was previously considered to be dedicated to professional translators because of technical problems, but now the translation machine has already become an accessible tool that people can easily use in daily life.
      This study will analyze the implementation of machine translation between Chinese and Korean by targeting at Papago, which is a translation machine developed by Korean famous online company Naver that Chinese-speaking learners can easily have access to, and Baidu, which is a well-known translation machine in China. Besides, in order to evaluate the translation accuracy between Chinese and Korean of the famous Google Translate which is currently used worldwide, Google Translate is also included in the study. Ten translators were invited to evaluate the translation results of the machine and in this way the accuracy of the machine translation has been obtained.
      The analysis objects selected in this study are representative cultural vocabulary arising from language differences: idioms, poems, proverbs and proper nouns, all of which are cultural vocabulary that are the most dependent on the culture in translation.
      Although the object of evaluation is linguistic expression, considering the contextual information of translation and interpretation, the entire sentence containing cultural vocabulary is presented to the evaluator so that they can realize the environment in which the expression is used. In this study, the evaluation scores, evaluation items, and evaluation criteria of the translation are listed, and the results are obtained from a combination of all these factors.
      This study reveals the development direction of machine translation and seeks the common development between translators and machines, through the comparison between machine translation and human translation. Therefore, if the translation pattern such as the error pattern of the translation machine can be understood before using, it is expected to further improve the efficiency.
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      The development of translation machines represented by machine translation and AI translation has recently become a hot topic in the society. Particularly, in recent years, the accuracy and fluency of translation machines have been greatly improved th...

      The development of translation machines represented by machine translation and AI translation has recently become a hot topic in the society. Particularly, in recent years, the accuracy and fluency of translation machines have been greatly improved thanks to the use of neural network technology (NMT,Neural Machine Translation), and translation machines have become the main focus of public attention.
      In addition, the translation machine was previously considered to be dedicated to professional translators because of technical problems, but now the translation machine has already become an accessible tool that people can easily use in daily life.
      This study will analyze the implementation of machine translation between Chinese and Korean by targeting at Papago, which is a translation machine developed by Korean famous online company Naver that Chinese-speaking learners can easily have access to, and Baidu, which is a well-known translation machine in China. Besides, in order to evaluate the translation accuracy between Chinese and Korean of the famous Google Translate which is currently used worldwide, Google Translate is also included in the study. Ten translators were invited to evaluate the translation results of the machine and in this way the accuracy of the machine translation has been obtained.
      The analysis objects selected in this study are representative cultural vocabulary arising from language differences: idioms, poems, proverbs and proper nouns, all of which are cultural vocabulary that are the most dependent on the culture in translation.
      Although the object of evaluation is linguistic expression, considering the contextual information of translation and interpretation, the entire sentence containing cultural vocabulary is presented to the evaluator so that they can realize the environment in which the expression is used. In this study, the evaluation scores, evaluation items, and evaluation criteria of the translation are listed, and the results are obtained from a combination of all these factors.
      This study reveals the development direction of machine translation and seeks the common development between translators and machines, through the comparison between machine translation and human translation. Therefore, if the translation pattern such as the error pattern of the translation machine can be understood before using, it is expected to further improve the efficiency.

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      참고문헌 (Reference)

      1 금지아, "한중 번역에서의 문화소 번역 전략" 한국번역학회 16 (16): 7-26, 2015

      2 이상빈, "학부 번역전공자의 구글 기계번역 포스트에디팅에 관한 현상학 연구" 통번역연구소 22 (22): 117-143, 2018

      3 조선비즈, "인공지능이 쓴 소설, 인간의 심장을 두드릴 수 있을까"

      4 이근희, "이근희의 번역산책 -번역투에서 번역전략까지" 한국문화사 2005

      5 Jeremy Munday, "번역학 입문-이론과 적용" 한국외국어대학교 출판부 2006

      6 뉴시스, "바둑은 져도 번역은 이긴다…인간, AI에 압승"

      7 김도훈, "문화소의 부등성 보상을 위한 번역전략:부산 관광지 안내 표지판 및 책자를 중심으로" 한국번역학회 7 (7): 31-51, 2006

      8 김도훈, "문화소 번역에서의 인지적 축적물의 역할 및 번역전략" 한국통역번역학회 8 (8): 3-29, 2006

      9 전기정, "문학번역에서의 문화소와 번역 전략 ―『阿Q正傳』을 중심으로" 중국어문학연구회 (51) : 275-299, 2008

      10 마승혜, "기계화되기 어려운 인간 능력과 문학번역 능력 비교․고찰 및 논의" 통번역연구소 21 (21): 55-77, 2017

      1 금지아, "한중 번역에서의 문화소 번역 전략" 한국번역학회 16 (16): 7-26, 2015

      2 이상빈, "학부 번역전공자의 구글 기계번역 포스트에디팅에 관한 현상학 연구" 통번역연구소 22 (22): 117-143, 2018

      3 조선비즈, "인공지능이 쓴 소설, 인간의 심장을 두드릴 수 있을까"

      4 이근희, "이근희의 번역산책 -번역투에서 번역전략까지" 한국문화사 2005

      5 Jeremy Munday, "번역학 입문-이론과 적용" 한국외국어대학교 출판부 2006

      6 뉴시스, "바둑은 져도 번역은 이긴다…인간, AI에 압승"

      7 김도훈, "문화소의 부등성 보상을 위한 번역전략:부산 관광지 안내 표지판 및 책자를 중심으로" 한국번역학회 7 (7): 31-51, 2006

      8 김도훈, "문화소 번역에서의 인지적 축적물의 역할 및 번역전략" 한국통역번역학회 8 (8): 3-29, 2006

      9 전기정, "문학번역에서의 문화소와 번역 전략 ―『阿Q正傳』을 중심으로" 중국어문학연구회 (51) : 275-299, 2008

      10 마승혜, "기계화되기 어려운 인간 능력과 문학번역 능력 비교․고찰 및 논의" 통번역연구소 21 (21): 55-77, 2017

      11 "기계번역기의 역사와 발전, 카카오AI리포트 Vol8"

      12 장애리, "국내 기계 통번역의 발전 현황 분석: 한·중 언어 쌍을 중심으로" 한국번역학회 18 (18): 171-206, 2017

      13 글로벌이코노미, "MS의 AI ‘중영 번역’ 기술 인간 능력에 필적… ‘뉴태스크 2017’로 불리는 일련의 테스트 통해 검증"

      14 SUN, Dongyun, "Application of Post-Editing in Foreign Language Teaching: Problems and Challenges" 13 (13): 1-5, 2017

      15 컴퓨터월드, "AI 통번역의 진화"

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      학술지 이력

      학술지 이력
      연월일 이력구분 이력상세 등재구분
      2027 평가예정 재인증평가 신청대상 (재인증)
      2021-01-01 평가 등재학술지 유지 (재인증) KCI등재
      2018-01-01 평가 등재학술지 선정 (계속평가) KCI등재
      2016-01-01 평가 등재후보학술지 선정 (신규평가) KCI등재후보
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      기준연도 WOS-KCI 통합IF(2년) KCIF(2년) KCIF(3년)
      2016 0 0 0
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