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English Translation Based on Neural Machine Translation Using Transformer

첫 페이지 보기
  • 발행기관
    한국차세대컴퓨팅학회 바로가기
  • 간행물
    한국차세대컴퓨팅학회 학술대회 바로가기
  • 통권
    The 8th International Conference on Next Generation Computing 2022 (2022.10)바로가기
  • 페이지
    pp.201-204
  • 저자
    Jongho Won, Min Dong Jin, Deok-Hwan Kim
  • 언어
    영어(ENG)
  • URL
    https://www.earticle.net/Article/A419774

원문정보

초록

영어
Machine translation is one of the classic sub-fields of natural language processing, a field that has been studied for a long time. There are several methods related to machine translation, and neural machine translation is one of them. Neural machine translation is a method that translates the source sentence to the target sentence through a neural network model. Recently, the transformer model using the attention mechanism has become the SOTA technique in the field. In this research, the transformer model using the attention mechanism is trained through 2 parallel corpora: English-German and English-Korean. The results of translations are evaluated with a BLEU score for each. The transformer shows an 8.60 BLEU score when trained by the English-German parallel corpora, and a 0.43 BLEU score in the case of English-Korean. It seems like the reason why the performance of English-German translations is higher than the performance of English-Korean translations is that English and Germany are in the Germanic language family, which is the same. In contrast, unlike English, Korean belongs to Altaic or Isolated languages and has different linguistic characteristics. The performance of the transformer is also affected by the quality of the parallel corpus used for training. It can be interpreted that it is necessary to secure a higher quality English-Korean parallel corpus.

목차

Abstract
I. INTRODUCTION
II. BACKGROUNDS
A. Rule-based machine translation
B. Statistical machine translation
C. Neural machine translation
III. METHOD
A. Dataset
B. Experiment Environment
IV. RESULT
V. DISCUSSION
VI. CONCLUSION AND FUTURE WORK
REFERENCES

키워드

machine translation attention mechanism transformer neural machine translation parallel corpus BLEU

저자

  • Jongho Won [ Department of Electrical and Computer Engineering Inha University ]
  • Min Dong Jin [ Department of Electrical and Computer Engineering Inha University ]
  • Deok-Hwan Kim [ Department of Electrical and Computer Engineering Inha University ] Corresponding Author

참고문헌

자료제공 : 네이버학술정보

간행물 정보

발행기관

  • 발행기관명
    한국차세대컴퓨팅학회 [Korean Institute of Next Generation Computing]
  • 설립연도
    2005
  • 분야
    공학>컴퓨터학
  • 소개
    본 학회는 차세대 PC 및 그 관련분야의 학술활동을 통하여 차세대 PC의 학문 및 기술발전을 도모하고 산업발전 및 국제협력 증진을 목적으로 한다.

간행물

  • 간행물명
    한국차세대컴퓨팅학회 학술대회
  • 간기
    반년간
  • 수록기간
    2021~2025
  • 십진분류
    KDC 566 DDC 004

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