Decoding optimization for Chinese-english machine translation via a dependent syntax language model

Authors:
Ying Liu;Zhengtao Yu;Tao Zhang;Xing Zhao
Affiliations:
School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China;School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China and Key Laboratory of Intelligent Information Processing, Kunming University of Scien ...;School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China;School of Information Engineering and Automation, Kunming University of Science and Technology, Kunming, China and Key Laboratory of Intelligent Information Processing, Kunming University of Scien ...
Venue:
AICI'11 Proceedings of the Third international conference on Artificial intelligence and computational intelligence - Volume Part III
Year:
2011

Citing 5
Cited 0

Stochastic inversion transduction grammars and bilingual parsing of parallel corpora

Computational Linguistics
A syntax-based statistical translation model

ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Word alignment with cohesion constraint

NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
A hierarchical phrase-based model for statistical machine translation

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Dependency treelet translation: syntactically informed phrasal SMT

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

Decoding is a core process of the statistical machine translation, and determines the final results of it. In this paper, a decoding optimization for Chinese-English SMT with a dependent syntax language model was proposed, in order to improve the performance of the decoder in Chinese-English statistical machine translation. The data set was firstly trained in a dependent language model, and then calculated scores of NBEST list from decoding with the model. According to adding the original score of NBEST list from the decoder, the NBEST list of machine translation was reordered. The experimental results show that this approach can optimize the decoder results, and to some extent, improve the translation quality of the machine translation system.