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|Title:||Fast translation rule matching for syntax-based statistical machine translation|
|Authors:||Zhang, H. |
|Source:||Zhang, H.,Zhang, M.,Li, H.,Tan, C.L. (2009). Fast translation rule matching for syntax-based statistical machine translation. EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009 : 1037-1045. ScholarBank@NUS Repository.|
|Abstract:||In a linguistically-motivated syntax-based translation system, the entire translation process is normally carried out in two steps, translation rule matching and target sentence decoding using the matched rules. Both steps are very time-consuming due to the tremendous number of translation rules, the exhaustive search in translation rule matching and the complex nature of the translation task itself. In this paper, we propose a hyper-tree-based fast algorithm for translation rule matching. Experimental results on the NIST MT-2003 Chinese-English translation task show that our algorithm is at least 19 times faster in rule matching and is able to help to save 57% of overall translation time over previous methods when using large fragment translation rules. © 2009 ACL and AFNLP.|
|Source Title:||EMNLP 2009 - Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: A Meeting of SIGDAT, a Special Interest Group of ACL, Held in Conjunction with ACL-IJCNLP 2009|
|Appears in Collections:||Staff Publications|
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