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> 한국언어문화교육학회 > 언어와 문화 > 17권 1호

딥러닝 언어모델의 한국어 학습자 말뭉치 원어민성 판단 결과 분석 연구

A Study on the Judgment of Nativelikeness of Korean Learner Corpus by Deep Learning Language Model

이진 ( Lee Jin ) , 정진경 ( Jung Jinkyung ) , 김한샘 ( Kim Hansaem )

- 발행기관 : 한국언어문화교육학회

- 발행년도 : 2021

- 간행물 : 언어와 문화, 17권 1호

- 페이지 : pp.155-177 ( 총 23 페이지 )


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6,300
논문제목
초록(외국어)
The present study aims to analyze how deep learning judges nativelikeness in the corpus of native Korean speakers and Korean learners. To this end, a deep learning model that classifies sentences of native Korean speakers and Korean learners was built, and the criteria for determining nativelikeness between deep learning and humans were compared and analyzed in terms of error analysis. As a result of the analysis, the accuracy of the deep learning model built in this study was found to be 91%, which means that 91 sentences out of 100 sentences were accurately classified whether they were written by the native speaker or by the learner. In addition, since the error annotation result of the learner corpus is a projected result of human judgment of nativelikeness, the similarities and differences of the criteria for determining nativelikeness were described in detail by comparing it with the test data verification result of deep learning. The results of this study will be an important basis for clarifying what the nativelikeness of native Korean speakers is and for objectively judging the nativelikeness of the language produced by Korean learners.(Yonsei University)

논문정보
  • - 주제 : 어문학분야 > 언어학
  • - 발행기관 : 한국언어문화교육학회
  • - 간행물 : 언어와 문화, 17권 1호
  • - 발행년도 : 2021
  • - 페이지 : pp.155-177 ( 총 23 페이지 )
  • - UCI(KEPA) :
저널정보
  • - 주제 : 어문학분야 > 언어학
  • - 성격 : 학술지
  • - 간기 : 계간
  • - 국내 등재 : KCI 등재
  • - 해외 등재 : -
  • - ISSN : 1738-3641
  • - 수록범위 : 2004–2021
  • - 수록 논문수 : 602