Volume 2, Issue 2, June 2017, Page: 73-77
The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation
Jang Chung-Hyok, Faculty of Foreign Language and Literature, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea
Kim Kwang-Hyok, College of Computer Science, Kim Il Sung University, Pyongyang, Democratic People’s Republic of Korea
Received: Feb. 2, 2017;       Accepted: Feb. 25, 2017;       Published: Mar. 15, 2017
DOI: 10.11648/j.mlr.20170202.15      View  1277      Downloads  59
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.
Keywords
Machine Translation, Negative Sentence, Negation, EKMT, Rule-Based Machine Translation
To cite this article
Jang Chung-Hyok, Kim Kwang-Hyok, The Improvement of Negative Sentences Translation in English-to-Korean Machine Translation, Machine Learning Research. Vol. 2, No. 2, 2017, pp. 73-77. doi: 10.11648/j.mlr.20170202.15
Copyright
Copyright © 2017 Authors retain the copyright of this article.
This article is an open access article distributed under the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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