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Computational Intelligence and Neuroscience
Volume 2016, Article ID 9821608, 11 pages
Research Article

A Character Level Based and Word Level Based Approach for Chinese-Vietnamese Machine Translation

1Faculty of Information Technology, Ton Duc Thang University, Ho Chi Minh City 700000, Vietnam
2Faculty of Information Technology, VNU-HCM University of Science, Ho Chi Minh City 700000, Vietnam

Received 11 March 2016; Accepted 8 May 2016

Academic Editor: Stefan Haufe

Copyright © 2016 Phuoc Tran et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.


Chinese and Vietnamese have the same isolated language; that is, the words are not delimited by spaces. In machine translation, word segmentation is often done first when translating from Chinese or Vietnamese into different languages (typically English) and vice versa. However, it is a matter for consideration that words may or may not be segmented when translating between two languages in which spaces are not used between words, such as Chinese and Vietnamese. Since Chinese-Vietnamese is a low-resource language pair, the sparse data problem is evident in the translation system of this language pair. Therefore, while translating, whether it should be segmented or not becomes more important. In this paper, we propose a new method for translating Chinese to Vietnamese based on a combination of the advantages of character level and word level translation. In addition, a hybrid approach that combines statistics and rules is used to translate on the word level. And at the character level, a statistical translation is used. The experimental results showed that our method improved the performance of machine translation over that of character or word level translation.