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Improving statistical machine translation using domain bilingual multiword expressions

Authors:

Yun HuangAuthors Info & Claims

MWE '09: Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications

Pages 47 - 54

Published: 06 August 2009 Publication History

Abstract

Multiword expressions (MWEs) have been proved useful for many natural language processing tasks. However, how to use them to improve performance of statistical machine translation (SMT) is not well studied. This paper presents a simple yet effective strategy to extract domain bilingual multiword expressions. In addition, we implement three methods to integrate bilingual MWEs to Moses, the state-of-the-art phrase-based machine translation system. Experiments show that bilingual MWEs could improve translation performance significantly.

References

[1]

Necip Fazil Ayan and Bonnie J. Dorr. 2006. Going beyond aer: an extensive analysis of word alignments and their impact on mt. In Proceedings of the 44th Annual Meeting of the Association for Computational Linguistics, pages 9--16.

Digital Library

[2]

Timothy Baldwin, Colin Bannard, Takaaki Tanaka, and Dominic Widdows. 2003. An empirical model of multiword expression decomposability. In Proceedings of the ACL-2003 Workshop on Multiword Expressions: Analysis, Acquisiton and Treatment, pages 89--96.

Digital Library

[3]

Colin Bannard. 2007. A measure of syntactic flexibility for automatically identifying multiword expressions in corpora. In Proceedings of the ACL Workshop on A Broader Perspective on Multiword Expressions, pages 1--8.

Digital Library

[4]

Peter F. Brown, Stephen Della Pietra, Vincent J. Della Pietra, and Robert L. Mercer. 1993. The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics, 19(2):263--311.

Digital Library

[5]

Baobao Chang, Pernilla Danielsson, and Wolfgang Teubert. 2002. Extraction of translation unit from chinese-english parallel corpora. In Proceedings of the first SIGHAN workshop on Chinese language processing, pages 1--5.

Digital Library

[6]

Stanley F. Chen and Joshua Goodman. 1998. Am empirical study of smoothing techniques for language modeling. Technical report.

[7]

Michael Collins, Philipp Koehn, and Ivona Kučerová. 2005. Clause restructuring for statistical machine translation. In Proceedings of the 43rd Annual Meeting on Association for Computational Linguistics, pages 531--540.

Digital Library

[8]

Michael Collins. 2002. Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. In Proceedings of the Empirical Methods in Natural Language Processing Conference, pages 1--8.

Digital Library

[9]

Tim Van de Cruys and Begoña Villada Moirón. 2007. Semantics-based multiword expression extraction. In Proceedings of the Workshop on A Broader Perspective on Multiword Expressions, pages 25--32.

Digital Library

[10]

Ted Dunning. 1993. Accurate methods for the statistics of surprise and coincidence. Computational Linguistics, 19(1):61--74.

Digital Library

[11]

Matthias Eck, Stephan Vogel, and Alex Waibel. 2004. Improving statistical machine translation in the medical domain using the unified medical language system. In Proceedings of the 20th international conference on Computational Linguistics table of contents, pages 792--798.

Digital Library

[12]

Afsaneh Fazly and Suzanne Stevenson. 2006. Automatically constructing a lexicon of verb phrase idiomatic combinations. In Proceedings of the EACL, pages 337--344.

[13]

Katerina T. Frantzi and Sophia Ananiadou. 1996. Extracting nested collocations. In Proceedings of the 16th conference on Computational linguistics, pages 41--46.

Digital Library

[14]

Alexander Fraser and Daniel Marcu. 2007. Measuring word alignment quality for statistical machine translation. Computational Linguistics, 33(3):293--303.

Digital Library

[15]

Philipp Koehn, Franz Josef Och, and Daniel Marcu. 2003. Statistical phrase-based translation. In Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology, pages 48--54.

Digital Library

[16]

Patrik Lambert and Rafael Banchs. 2005. Data inferred multi-word expressions for statistical machine translation. In Proceedings of Machine Translation Summit X, pages 396--403.

[17]

Patrik Lambert and Rafael Banchs. 2006. Grouping multi-word expressions according to part-of-speech in statistical machine translation. In Proceedings of the Workshop on Multi-word-expressions in a multilingual context, pages 9--16.

[18]

Adam Lopez and Philip Resnik. 2006. Word-based alignment, phrase-based translation: What's the link? In proceedings of the 7th conference of the association for machine translation in the Americas: visions for the future of machine translation, pages 90--99.

[19]

Shengfen Luo and Maosong Sun. 2003. Two-character chinese word extraction based on hybrid of internal and contextual measures. In Proceedings of the second SIGHAN workshop on Chinese language processing, pages 24--30.

Digital Library

[20]

Franz Josef Och. 2002. Statistical Machine Translation: From Single-Word Models to Alignment Templates. Ph.d. thesis, Computer Science Department, RWTH Aachen, Germany.

[21]

Patrick Pantel and Dekang Lin. 2001. A statistical corpus based term extractor. In AI '01: Proceedings of the 14th Biennial Conference of the Canadian Society on Computational Studies of Intelligence, pages 36--46.

Digital Library

[22]

Kishore Papineni, Salim Roukos, Todd Ward, and Weijing Zhu. 2002. Bleu: a method for automatic evaluation of machine translation. In Proceedings of the 40th Annual Conference of the Association for Computational Linguistics, pages 311--318.

Digital Library

[23]

Scott Songlin Piao, Paul Rayson, Dawn Archer, and Tony McEnery. 2005. Comparing and combining a semantic tagger and a statistical tool for mwe extraction. Computer Speech and Language, 19(4):378--397.

Digital Library

[24]

Ivan A. Sag, Timothy Baldwin, Francis Bond, Ann Copestake, and Dan Flickinger. 2002. Multiword expressions: A pain in the neck for nlp. In Proceedings of the 3th International Conference on Intelligent Text Processing and Computational Linguistics(CICLing-2002), pages 1--15.

Digital Library

[25]

Takaaki Tanaka and Timothy Baldwin. 2003. Noun-noun compound machine translation: A feasibility study on shallow processing. In Proceedings of the ACL-2003 Workshop on Multiword Expressions: Analysis, Acquisition and Treatment, pages 17--24.

Digital Library

[26]

Hua Wu, Haifeng Wang, and Chengqing Zong. 2008. Domain adaptation for statistical machine translation with domain dictionary and monolingual corpora. In Proceedings of Conference on Computational Linguistics (COLING), pages 993--1000.

Digital Library

Cited By

Cordeiro SVillavicencio AIdiart MRamisch C(2019)Unsupervised compositionality prediction of nominal compoundsComputational Linguistics10.1162/coli_a_0034145:1(1-57)Online publication date: 17-May-2019
https://dl.acm.org/doi/10.1162/coli_a_00341
Xiong DMeng FLiu Q(2019)Topic-based term translation models for statistical machine translationArtificial Intelligence10.1016/j.artint.2015.12.002232:C(54-75)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1016/j.artint.2015.12.002
Dramé KDiallo GDelva FDartigues JMouillet ESalamon RMougin F(2018)Reuse of termino-ontological resources and text corpora for building a multilingual domain ontologyJournal of Biomedical Informatics10.1016/j.jbi.2013.12.01348:C(171-182)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1016/j.jbi.2013.12.013
Show More Cited By

Index Terms

Improving statistical machine translation using domain bilingual multiword expressions
1. Applied computing
  1. Document management and text processing
2. Computing methodologies
  1. Artificial intelligence
    1. Natural language processing
      1. Machine translation

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Information & Contributors

Information

Published In

cover image DL Hosted proceedings

MWE '09: Proceedings of the Workshop on Multiword Expressions: Identification, Interpretation, Disambiguation and Applications

August 2009

80 pages

ISBN:9781932432602

General Chairs:
Dimitra Anastasiou
Localisation Research Centre, Limerick University, Ireland
,
Chikara Hashimoto
National Institute of Information and Communications Technology, Japan
,
Preslav Nakov
National University of Singapore, Singapore
,
Su Nam Kim
University of Melbourne, Australia

Publisher

Association for Computational Linguistics

United States

Publication History

Published: 06 August 2009

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Overall Acceptance Rate 31 of 69 submissions, 45%

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Citations

Cited By

Cordeiro SVillavicencio AIdiart MRamisch C(2019)Unsupervised compositionality prediction of nominal compoundsComputational Linguistics10.1162/coli_a_0034145:1(1-57)Online publication date: 17-May-2019
https://dl.acm.org/doi/10.1162/coli_a_00341
Xiong DMeng FLiu Q(2019)Topic-based term translation models for statistical machine translationArtificial Intelligence10.1016/j.artint.2015.12.002232:C(54-75)Online publication date: 4-Jan-2019
https://dl.acm.org/doi/10.1016/j.artint.2015.12.002
Dramé KDiallo GDelva FDartigues JMouillet ESalamon RMougin F(2018)Reuse of termino-ontological resources and text corpora for building a multilingual domain ontologyJournal of Biomedical Informatics10.1016/j.jbi.2013.12.01348:C(171-182)Online publication date: 26-Dec-2018
https://dl.acm.org/doi/10.1016/j.jbi.2013.12.013
Pal SBandyopadhyay S(2012)Bootstrapping method for chunk alignment in phrase based SMTProceedings of the Joint Workshop on Exploiting Synergies between Information Retrieval and Machine Translation (ESIRMT) and Hybrid Approaches to Machine Translation (HyTra)10.5555/2387956.2387969(93-100)Online publication date: 23-Apr-2012
https://dl.acm.org/doi/10.5555/2387956.2387969
Wang LLiu R(2011)A rapid method to extract multiword expressions with statistic measures and linguistic rulesProceedings of the 2011 international conference on Web information systems and mining - Volume Part II10.5555/2045753.2045789(234-241)Online publication date: 24-Sep-2011
https://dl.acm.org/doi/10.5555/2045753.2045789
Watrin PFrançois TKordoni VRamisch CVillavicencio A(2011)An n-gram frequency database reference to handle MWE extraction in NLP applicationsProceedings of the Workshop on Multiword Expressions: from Parsing and Generation to the Real World10.5555/2021121.2021139(83-91)Online publication date: 23-Jun-2011
https://dl.acm.org/doi/10.5555/2021121.2021139
Bejček EStraňák PZeman D(2011)Influence of treebank design on representation of multiword expressionsProceedings of the 12th international conference on Computational linguistics and intelligent text processing - Volume Part I10.5555/1964799.1964801(1-14)Online publication date: 20-Feb-2011
https://dl.acm.org/doi/10.5555/1964799.1964801
Carpuat MDiab MKaplan R(2010)Task-based evaluation of multiword expressionsHuman Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics10.5555/1857999.1858028(242-245)Online publication date: 2-Jun-2010
https://dl.acm.org/doi/10.5555/1857999.1858028

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