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      중한 문화소 번역에서의 포스트에디팅 전략 연구

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      https://www.riss.kr/link?id=T17377171

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      다국어 초록 (Multilingual Abstract) kakao i 다국어 번역

      This study examines the translation of Culturemes in Chinese–Korean artificial intelligence (AI) literary translation and proposes practical post-editing (PE) guidelines to improve translation quality. Using a Chinese novel as the source text, the study analyzes how Culturemes are rendered in ChatGPT’s Korean translations and identifies cases where post-editing is required due to insufficient equivalence at the lexical, sentential, or contextual level.
      Based on an integrated classification framework, a total of 352 Culturemes were identified in the source text, of which 181 items (51.42%) were classified as requiring post-editing. Quantitative analysis shows that social-specific terms exhibited the highest need for post-editing, while idiomatic expressions demonstrated relatively stable translation performance. Drawing on Aixelá’s preservation–substitution framework, this study applies eight post-editing strategies, including transliteration, intratextual and extratextual explanation, paraphrasing, domestication, generalization, and omission, to representative translation examples.
      To evaluate the effectiveness of the proposed strategies, a survey was conducted with 30 native Korean speakers. The results indicate a consistent preference for post-edited translations over raw AI outputs, suggesting that the proposed strategies contribute positively to translation acceptability. Based on these findings, the study presents a set of practical post-editing guidelines for Cultureme translation, offering empirical support for improving the quality of Chinese–Korean AI literary translation.
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      This study examines the translation of Culturemes in Chinese–Korean artificial intelligence (AI) literary translation and proposes practical post-editing (PE) guidelines to improve translation quality. Using a Chinese novel as the source text, the s...

      This study examines the translation of Culturemes in Chinese–Korean artificial intelligence (AI) literary translation and proposes practical post-editing (PE) guidelines to improve translation quality. Using a Chinese novel as the source text, the study analyzes how Culturemes are rendered in ChatGPT’s Korean translations and identifies cases where post-editing is required due to insufficient equivalence at the lexical, sentential, or contextual level.
      Based on an integrated classification framework, a total of 352 Culturemes were identified in the source text, of which 181 items (51.42%) were classified as requiring post-editing. Quantitative analysis shows that social-specific terms exhibited the highest need for post-editing, while idiomatic expressions demonstrated relatively stable translation performance. Drawing on Aixelá’s preservation–substitution framework, this study applies eight post-editing strategies, including transliteration, intratextual and extratextual explanation, paraphrasing, domestication, generalization, and omission, to representative translation examples.
      To evaluate the effectiveness of the proposed strategies, a survey was conducted with 30 native Korean speakers. The results indicate a consistent preference for post-edited translations over raw AI outputs, suggesting that the proposed strategies contribute positively to translation acceptability. Based on these findings, the study presents a set of practical post-editing guidelines for Cultureme translation, offering empirical support for improving the quality of Chinese–Korean AI literary translation.

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      목차 (Table of Contents)

      • 1. 서론 1
      • 1.1 연구 목적 1
      • 1.2 선행연구 4
      • 1.3 연구 방법 16
      • 1. 서론 1
      • 1.1 연구 목적 1
      • 1.2 선행연구 4
      • 1.3 연구 방법 16
      • 2. 이론적 배경 20
      • 2.1 문화소의 정의 및 분류 20
      • 2.2 포스트에디팅 대상의 선정 기준 25
      • 2.3 문화소의 포스트에디팅 전략 29
      • 3. 문화소의 포스트에디팅 전략 37
      • 3.1 포스트에디팅 대상의 선정과 통계 37
      • 3.1.1 문화소 분포 37
      • 3.1.2 포스트에디팅 대상 분포 38
      • 3.1.3 유형별 문화소 포스트에디팅 대상 분포 39
      • 3.2 보존 방식의 포스트에디팅 전략 분석 42
      • 3.2.1 음역 42
      • 3.2.2 언어 중심 번역 53
      • 3.2.3 텍스트 외적 설명 57
      • 3.2.4 텍스트 내적 설명 64
      • 3.3 대체 방식의 포스트에디팅 전략 분석 67
      • 3.3.1 풀어쓰기 68
      • 3.3.2 자국어화 74
      • 3.3.3 일반화 84
      • 3.3.4 생략 88
      • 3.4 문화소 포스트에디팅 가이드라인의 제안 및 효과 검증 92
      • 4. 결론 101
      • 참고문헌 105
      • 부록 1 109
      • 부록 2 123
      • ABSTRACT 137
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