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The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation

Received: 2 February 2017     Accepted: 25 February 2017     Published: 15 March 2017
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Abstract

This paper describes the translation algorithm of English negative sentences in rule-based English-Korean Machine Translation (EKMT). The proposed algorithm is based on the comparative study of the linguistic characteristics of English and Korean negative sentences. The earlier versions of machine translation system which is under development by our research team, failed to translate English negative sentences into accurate Korean equivalents. On the basis of the comparative linguistic research on negation in English and Korean, a new translation algorithm of the English negative sentences was established and evaluated.

Published in Machine Learning Research (Volume 2, Issue 2)
DOI 10.11648/j.mlr.20170202.15
Page(s) 73-77
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2017. Published by Science Publishing Group

Keywords

Machine Translation, Negative Sentence, Negation, EKMT, Rule-Based Machine Translation

References
[1] Ronald Carter & Michael McCarthy (2006). Cambridge Grammar of English, Cambridge University Press.
[2] John Hutchins (2009). Trends in Machine Translation Research, University of East Anglia, Norwich, UK.
[3] Christopher D. Manning & Hinrich Schütze (1999) Foundations of Statistical Natural Language Processing, The MIT Press.
[4] David Crystal (2008) A Dictionary of Linguistics and Phonetics, Sixth Edition, Blackwell Publishing.
[5] John Hutchins (2007). Machine Translation: a concise history. In Computer Aided Translation: Theory and Practice, C. S. Wai (ed.). Chinese University of Hong Kong.
[6] John Hutchins & Somer, H. L (1992). An Introduction to Machine Translation. Academic Press, London.
[7] Slav Petrov (2012) Coarse-to-Fine Natural Language Processing. Springer-Verlag Berlin Heidelberg.
[8] Karsten Konrad (2004) Model Generation for Natural Language Interpretation and Analysis. Springer-Verlag Berlin Heidelberg.
[9] Yorick Wilks (2009) Machine Translation: Its Scope and Limits. Springer.
[10] Olive, J. (Ed), Christianson, C. (Ed), McCary, J. (Ed) (2011) Handbook of Natural Language Processing and Machine Translation. Springer.
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  • APA Style

    Jang Chung-Hyok, Kim Kwang-Hyok. (2017). The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation. Machine Learning Research, 2(2), 73-77. https://doi.org/10.11648/j.mlr.20170202.15

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    ACS Style

    Jang Chung-Hyok; Kim Kwang-Hyok. The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation. Mach. Learn. Res. 2017, 2(2), 73-77. doi: 10.11648/j.mlr.20170202.15

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    AMA Style

    Jang Chung-Hyok, Kim Kwang-Hyok. The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation. Mach Learn Res. 2017;2(2):73-77. doi: 10.11648/j.mlr.20170202.15

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  • @article{10.11648/j.mlr.20170202.15,
      author = {Jang Chung-Hyok and Kim Kwang-Hyok},
      title = {The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation},
      journal = {Machine Learning Research},
      volume = {2},
      number = {2},
      pages = {73-77},
      doi = {10.11648/j.mlr.20170202.15},
      url = {https://doi.org/10.11648/j.mlr.20170202.15},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.mlr.20170202.15},
      abstract = {This paper describes the translation algorithm of English negative sentences in rule-based English-Korean Machine Translation (EKMT). The proposed algorithm is based on the comparative study of the linguistic characteristics of English and Korean negative sentences. The earlier versions of machine translation system which is under development by our research team, failed to translate English negative sentences into accurate Korean equivalents. On the basis of the comparative linguistic research on negation in English and Korean, a new translation algorithm of the English negative sentences was established and evaluated.},
     year = {2017}
    }
    

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  • TY  - JOUR
    T1  - The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation
    AU  - Jang Chung-Hyok
    AU  - Kim Kwang-Hyok
    Y1  - 2017/03/15
    PY  - 2017
    N1  - https://doi.org/10.11648/j.mlr.20170202.15
    DO  - 10.11648/j.mlr.20170202.15
    T2  - Machine Learning Research
    JF  - Machine Learning Research
    JO  - Machine Learning Research
    SP  - 73
    EP  - 77
    PB  - Science Publishing Group
    SN  - 2637-5680
    UR  - https://doi.org/10.11648/j.mlr.20170202.15
    AB  - This paper describes the translation algorithm of English negative sentences in rule-based English-Korean Machine Translation (EKMT). The proposed algorithm is based on the comparative study of the linguistic characteristics of English and Korean negative sentences. The earlier versions of machine translation system which is under development by our research team, failed to translate English negative sentences into accurate Korean equivalents. On the basis of the comparative linguistic research on negation in English and Korean, a new translation algorithm of the English negative sentences was established and evaluated.
    VL  - 2
    IS  - 2
    ER  - 

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Author Information
  • Faculty of Foreign Language and Literature, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea

  • College of Computer Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea

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