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Published in: International Journal of Machine Learning and Cybernetics 1/2017

18-01-2015 | Original Article

Chinese-Naxi machine translation method based on Naxi dependency language model

Authors: Shengxiang Gao, Xiuzhen Yang, Zhengtao Yu, Xiao Pan, Jianyi Guo

Published in: International Journal of Machine Learning and Cybernetics | Issue 1/2017

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Abstract

To make use of the syntactic characteristic of Naxi language effectively, in this paper, a Chinese-Naxi machine translation method based on Naxi dependency language model is proposed. The method, firstly, makes dependency parsing on the Chinese sentence, and extracts Chinese-Naxi dependency tree-to-string translation templates. Secondly, it decodes Naxi Sentence by using the templates, and generates n-best candidate sentences. Thirdly, it makes dependency parsing on each of the candidate Naxi sentences, and obtains a node sequence corresponding to the dependency relationships. Finally, it builds a Naxi dependency language model, with the help of the model, calculates and reorders each node from the sequence, and selects the final target sentence. The comparative experiments, on the proposed method, the existing tree-to-string translating method, Bruin and Mo-tse, show that the Chinese-Naxi machine translation method combined with the Naxi dependency language model can improve the translating accuracy effectively, and its BLEU-2 increases by 2 point than without the Naxi dependency language model.

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Metadata
Title
Chinese-Naxi machine translation method based on Naxi dependency language model
Authors
Shengxiang Gao
Xiuzhen Yang
Zhengtao Yu
Xiao Pan
Jianyi Guo
Publication date
18-01-2015
Publisher
Springer Berlin Heidelberg
Published in
International Journal of Machine Learning and Cybernetics / Issue 1/2017
Print ISSN: 1868-8071
Electronic ISSN: 1868-808X
DOI
https://doi.org/10.1007/s13042-014-0325-2

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