Earticle

초록

영어

This paper begins with the question. Is it possible that a machine can understand and evaluate the meaning of a text? Word2Vec is a neural network method of computing vector representations of words, which means the tool processes a text corpus and produces numeric vectors on the meanings of the words. This paper seeks to examine whether the automatic evaluation metrics, BLEUmodif and METEORmodif, enhanced by word2vec technology, are able to capture the meaning of translated texts better than their standard versions. To this end, first, five literary texts written in English were translated into Korean by 119 students. Then, these translations were evaluated by two professional translators/teachers and by five different automatic evaluation programs. These are standard versions of BLEU and METEOR as well as BLEUmodif and METEORmodif with the word2vec technology and finally Sent2Vec that computes sentence vector representations. For the sake of convenience, the last three systems are referred to as “embedding versions” in this study. The analysis shows that overall, the standard version of METEOR performed the best (grades: 0.838, ranking: 0.727), but at the level of individual texts, the embedding versions of BLEU and METEOR showed a higher correlation with human evaluation (four texts) than their standard versions (one text).

목차

1. 기계가 번역의 ‘의미’를 평가할 수 있을까
2. 기계는 ‘의미’를 어떻게 이해하는가
3. 기계는 번역을 어떻게 평가하는가
3.1. 형태의 평가 - BLEU, METEOR
3.2. 의미의 평가 - 임BLEU, 임METEOR, S2V
4. 실험
4.1. 텍스트
4.2. 인간평가
4.3. 자동평가
5. 결과
5.1. 전체 텍스트 차원
5.2. 개별 텍스트 차원
6. 요약 및 토론
7. 제한점 및 향후 과제
참고문헌

키워드

저자

• 정혜연 [ Chung, Hye-yeon | 한국외대 통번역대학원 한독과 교수 ] 주저자, 교신저자
• 박헌일 [ Park, Hun-il | 사이버한국외국어대학교 영어학부 부교수 ] 공동저자
• 우경조 [ Woo, Kyong-jo | 한국외대 통번역대학원 한영과 겸임교수 ] 공동저자
• 서수영 [ Seo, Soo-young | 한림대학교 융합소프트웨어 학과 석사과정 ] 공동저자

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  통번역학연구 [Interpreting and Translation Studies]

• 간기

  계간

• pISSN

  1975-6321

• eISSN

  2713-8372

• 수록기간

  1997~2026

• 등재여부

  KCI 등재

• 십진분류

  KDC 717 DDC 400