Improve SMT quality with automatically extracted paraphrase rules

Authors:
Wei He;Hua Wu;Haifeng Wang;Ting Liu
Affiliations:
Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology;Baidu;Baidu;Research Center for Social Computing and Information Retrieval, Harbin Institute of Technology
Venue:
ACL '12 Proceedings of the 50th Annual Meeting of the Association for Computational Linguistics: Long Papers - Volume 1
Year:
2012

Citing 15
Cited 0

BLEU: a method for automatic evaluation of machine translation

ACL '02 Proceedings of the 40th Annual Meeting on Association for Computational Linguistics
Statistical phrase-based translation

NAACL '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology - Volume 1
Minimum error rate training in statistical machine translation

ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
Improved statistical alignment models

ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
A hierarchical phrase-based model for statistical machine translation

ACL '05 Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics
Improved statistical machine translation using paraphrases

HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Moses: open source toolkit for statistical machine translation

ACL '07 Proceedings of the 45th Annual Meeting of the ACL on Interactive Poster and Demonstration Sessions
Improved Statistical Machine Translation Using Monolingual Paraphrases

Proceedings of the 2008 conference on ECAI 2008: 18th European Conference on Artificial Intelligence
The back-translation score: automatic MT evaluation at the sentence level without reference translations

ACLShort '09 Proceedings of the ACL-IJCNLP 2009 Conference Short Papers
Source-language entailment modeling for translating unknown terms

ACL '09 Proceedings of the Joint Conference of the 47th Annual Meeting of the ACL and the 4th International Joint Conference on Natural Language Processing of the AFNLP: Volume 2 - Volume 2
Improved statistical machine translation using monolingually-derived paraphrases

EMNLP '09 Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing: Volume 1 - Volume 1
Paraphrase lattice for statistical machine translation

ACLShort '10 Proceedings of the ACL 2010 Conference Short Papers
Facilitating translation using source language paraphrase lattices

EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Example-based paraphrasing for improved phrase-based statistical machine translation

EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
Phrase clustering for smoothing TM probabilities: or, how to extract paraphrases from phrase tables

COLING '10 Proceedings of the 23rd International Conference on Computational Linguistics

Quantified Score

Hi-index	0.00

Visualization

Abstract

We propose a novel approach to improve SMT via paraphrase rules which are automatically extracted from the bilingual training data. Without using extra paraphrase resources, we acquire the rules by comparing the source side of the parallel corpus with the target-to-source translations of the target side. Besides the word and phrase paraphrases, the acquired paraphrase rules mainly cover the structured paraphrases on the sentence level. These rules are employed to enrich the SMT inputs for translation quality improvement. The experimental results show that our proposed approach achieves significant improvements of 1.6~3.6 points of BLEU in the oral domain and 0.5~1 points in the news domain.