Abstract
In statistical machine translation, many of the top-performing systems are phrase-based systems. This paper describes a phrase-based translation system and some improvements. We use more information to compute translation probability. The scaling factors of the log-linear models are estimated by the minimum error rate training that uses an evaluation criteria to balance BLEU and NIST scores. We extract phrase-template from initial phrases to deal with data sparseness and distortion problem through decoding. By re-ranking the n-best list of translations generated firstly, the system gets the final output. Some experiments concerned show that all these refinements are beneficial to get better results.
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
Preview
Unable to display preview. Download preview PDF.
References
Brown, P.F., Pietra, S.A.D., Pietra, V.J.D., Mercer, P.L.: The Mathematics of Statistical Machine Translation: Parameter Estimation. Computational Linguistics 19(2), 263–311 (1993)
Vogel, S., Zhang, Y., Huang, F., Tribble, A., Venugopal, A., Zhao, B., Waibel, A.: The CMU Statistical Machine Translation System. In: Proceedings of the Ninth Machine Translation Summit (2003)
Yamada, K., Knight: A Syntax-based Statistical Translation Model. In: Proc. of the 39th Annual Meeting of ACL (2001)
Yang, Z., Chen, Z., Pang, W., Wei, W., Xu, B.: The CASIA Phrase-Based Machine Translation System. In: IEEE NLPKE 2005, Wuhan, China, pp. 416–419 (2005)
Berger, A., Pietra, S.D., Pietra, D.: A Maximum Entropy Approach to Natural Language Processing. Computational Linguistics 22(1), 39–71 (1996)
Koehn, P., Och, F.J., Marcu, D.: Statistical Phrase-Based Translation. In: Proceedings of the Joint Conference on Human Language Technologies and the Annual Meeting of the North American Chapter of the Association of Computational Linguistics (2003)
Och, F.J., Ney, H.: The alignment template approach to statistical machine translation. Computational Linguistics 30, 417–449 (2004)
Chiang, D.: A hierarchical phrase-based model for statistical machine translation. In: Proceedings of ACL 2005, pp. 263–270 (2005)
OCH, F.J.: Minimum Error Rate Training in statistical machine translation. In: Proc. of the 41th Annual Meeting of the Association of Computational Linguistics(ACL), Sapporo, Japan (2003)
Press, W.H., Teukolsky, S., Vetterling, W.T., Flannery, B.P.: Numerical Recipes in C++. Cambrige University Press, Cambridge (2002)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2006 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Yang, Z., Pang, W., Du, J., Wei, W., Xu, B. (2006). Some Improvements in Phrase-Based Statistical Machine Translation. In: Huo, Q., Ma, B., Chng, ES., Li, H. (eds) Chinese Spoken Language Processing. ISCSLP 2006. Lecture Notes in Computer Science(), vol 4274. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11939993_71
Download citation
DOI: https://doi.org/10.1007/11939993_71
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-49665-6
Online ISBN: 978-3-540-49666-3
eBook Packages: Computer ScienceComputer Science (R0)