Abstract
Limited machine translation (LMT) is an unliterate automatic translation based on bilingual dictionary and sentence bank, and related algorithms can be widely used in natural language processing applications. This paper addresses the Japanese-Chinese LMT problem, proposes two syntactic hypotheses about Japanese language, and designs a fast-syntax-matching-based Japanese-Chinese (FSMJC) LMT algorithm. In which, the fast syntax matching function, a modified version of Levenshtein function, can approximately get the syntactic similarity after the efficient calculating of the formal similarity between two Japanese sentences. The experimental results show that the FSMJC LMT algorithm can achieve the preferable performance with greatly reduced time costs, and prove that our two syntactic hypotheses are effective on Japanese text.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
References
Brown, R.D.: The CMU-EBMT machine translation system. Mach. Transl. 25(2), 179–195 (2011)
Biçici, E., Dymetman, M.: Dynamic translation memory: using statistical machine translation to improve translation memory fuzzy matches. In: Gelbukh, A. (ed.) CICLing 2008. LNCS, vol. 4919, pp. 454–465. Springer, Heidelberg (2008). https://doi.org/10.1007/978-3-540-78135-6_39
Callison-Burch, C., Talbot, D., Osborne, M.: Statistical machine translation with word- and sentence-aligned parallel corpora. In: Proceedings of ACL 2004, the 42nd Meeting of the Association for Computational Linguistics, Barcelona, Spain, Main Volume, pp. 175–182 (2004)
Koehn, P., Senellart, J.: Fast approximate string matching with suffix arrays and A* parsing. In: Proceedings of AMTA 2010, The 9th Biennial Conference of the Association for Machine Translation in the Americas, Denver, Colorado, USA (2010)
Vanallemeersch, T., Vandeghinste, V.: Improving fuzzy matching through syntactic knowledge. In: Proceedings of the 36th Translating and the Computer Conference, Westminster, London, UK (2014)
Navarro, G., Baeza-Yates, R., Sutinen, E., Tarhio, J.: Indexing methods for approximate string matching. IEEE Data Eng. Bull. 24(4), 19–27 (2001)
Dan, H., Sudoh, K., Wu, X., Duh, K., Tsukada, H., Nagata, M.: Head finalization reordering for Chinese-to-Japanese machine translation. In: Proceedings of the Sixth Workshop on Syntax, Semantics and Structure in Statistical Translation, Stroudsburg, PA, USA, pp. 57–66 (2012)
Chu, C., Nakazawa, T., Kawahara, D., Kurohashi, S.: Chinese-Japanese Machine Translation Exploiting Chinese Characters. ACM Transactions on Asian Language Information Processing, 12(4) (2013). Article 16
Lin, C.-Y., Och, F.J.: Orange: a method for evaluating automatic evaluation metrics for machine translation. In: Proceedings of the 20th International Conference on Computational Linguistics, Geneva, Switzerland (2004)
Acknowledgements
The research is supported by the Featured Innovation Project of Guangdong Province (No.2015KTSCX035), National Social Science Foundation of China (No.12BYY136) and the National Natural Science Foundation of China (No.61402119).
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2018 Springer International Publishing AG, part of Springer Nature
About this paper
Cite this paper
Liu, W., Wang, L., Zhang, X. (2018). Fast-Syntax-Matching-Based Japanese-Chinese Limited Machine Translation. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2016. Lecture Notes in Computer Science(), vol 9624. Springer, Cham. https://doi.org/10.1007/978-3-319-75487-1_6
Download citation
DOI: https://doi.org/10.1007/978-3-319-75487-1_6
Published:
Publisher Name: Springer, Cham
Print ISBN: 978-3-319-75486-4
Online ISBN: 978-3-319-75487-1
eBook Packages: Computer ScienceComputer Science (R0)