Translation model size reduction for hierarchical phrase-based statistical machine translation

Seung Wook Lee, Dongdong Zhang, Mu Li, Ming Zhou, Hae-Chang Rim

Research output: Chapter in Book/Report/Conference proceedingConference contribution

7 Citations (Scopus)

Abstract

In this paper, we propose a novel method of reducing the size of translation model for hierarchical phrase-basedmachine translation systems. Previous approaches try to prune infrequent entries or unreliable entries based on statistics, but cause a problem of reducing the translation coverage. On the contrary, the proposed method try to prune only ineffective entries based on the estimation of the information redundancy encoded in phrase pairs and hierarchical rules, and thus preserve the search space of SMT decoders as much as possible. Experimental results on Chinese-to- English machine translation tasks show that our method is able to reduce almost the half size of the translation model with very tiny degradation of translation performance.

Original languageEnglish
Title of host publication50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference
Pages291-295
Number of pages5
Volume2
Publication statusPublished - 2012 Dec 1
Event50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Jeju Island, Korea, Republic of
Duration: 2012 Jul 82012 Jul 14

Other

Other50th Annual Meeting of the Association for Computational Linguistics, ACL 2012
CountryKorea, Republic of
CityJeju Island
Period12/7/812/7/14

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ASJC Scopus subject areas

  • Computational Theory and Mathematics
  • Software

Cite this

Lee, S. W., Zhang, D., Li, M., Zhou, M., & Rim, H-C. (2012). Translation model size reduction for hierarchical phrase-based statistical machine translation. In 50th Annual Meeting of the Association for Computational Linguistics, ACL 2012 - Proceedings of the Conference (Vol. 2, pp. 291-295)