Improving word alignment with bridge languages

EMNLP-CoNLL 2007 - Proceedings of the 2007 Joint Conference on Empirical Methods in Natural Language Processing and Computational Natural Language Learning

Volumn , Issue , 2007, Pages 42-50

  Kumar, Shankar ^a   Och, Franz ^a   Macherey, Wolfgang ^a  

^a GOOGLE INC   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

PARALLEL TEXT; SIMPLE METHOD; STATISTICAL MACHINE TRANSLATION; WORD ALIGNMENT;

ALIGNMENT; COMPUTATIONAL LINGUISTICS; NATURAL LANGUAGE PROCESSING SYSTEMS;

TRANSLATION (LANGUAGES);

EID: 80053234163     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (32)

1. N. Ayan and B. Dorr. 2006. A maximum entropy approach to combining word alignments. In HLTNAACL, New York, New York.
2. S. Bangalore, V. Murdock, and G. Riccardi. 2002. Bootstrapping bilingual data using consensus translation for a multilingual instant messaging system. In COLING, Taipei, Taiwan.
3. L. Borin. 2000. You'll take the high road and I'll take thelow road: Using a third language to improve bilingual word alignment. In COLING, pages 97-103, Saarbrucken, Germany.
4. T. Brants, A. Popat, P. Xu, F. Och, and J. Dean. 2007. Large language models in machine translation. In EMNLP, Prague, Czech Republic.
5. P. F. Brown, S. A. Della Pietra, V. J. Della Pietra, and R. L. Mercer. 1993. The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics, 19(2):263-311.
6. Y. Deng and W. Byrne. 2005. HMM word and phrase alignment for statistical machine translation. In EMNLP, Vancouver, Canada.
7. EU, 2005. European Parliament Proceedings. http://www.europarl.europa.eu.
8. EU, 2007. JRC Acquis Corpus.http://langtech.jrc.it/JRCAcquis.html.
9. K. Filali and J. Bilmes. 2005. Leveraging multiple languages to improve statistical mt word alignments. In IEEE Workshop on Automatic Speech Recognition and Understanding, San Juan, Puerto Rico.
10. A. Fraser and D. Marcu. 2006a. Measuring word alignment quality for statistical machine translation. Technical Report ISI-TR-616, ISI/University of Southern California.
11. A. Fraser and D. Marcu. 2006b. Semi-supervised training for statistical word alignment. In ACL, pages 769- 776, Sydney, Australia.
12. N. Ge. 2004. Improvements in word alignments. In Presentation given at DARPA/TIDES workshop.
13. A. Ittycheriah and S. Roukos. 2005. A maximum entropy word aligner for arabic-english machine translation. In EMNLP, Vancouver, Canada.
14. P. Koehn, 2003. European Parliament Proceedings, Sentence Aligned. http://people.csail.mit.edu/koehn/publications/europarl/.
15. P. Koehn. 2004. Statistical significance tests for machine translation evaluation. In EMNLP, Barcelona, Spain.
16. S. Kumar and W. Byrne. 2004. Minimum Bayes-risk decoding for statistical machine translation. In HLTNAACL, pages 169-176, Boston, MA, USA.
17. W. Macherey and F. Och. 2007. An empirical study on computing consensus translations from multiple machine translation systems. In EMNLP, Prague, Czech Republic.
18. G. Mann and D. Yarowsky. 2001. Multipath translation lexicon induction via bridge languages. In NAACL, Pittsburgh, PA, USA.
19. J. Martin, R. Mihalcea, and T. Pedersen. 2005. Word alignment for languages with scarce resources. In ACL Workshop on Building and Using Parallel Texts, pages 65-74, Ann Arbor, MI, USA.
20. E. Matusov, R. Zens, and H. Ney. 2004. Symmetric word alignments for statistical machine translation. In COLING, Geneva, Switzerland.
21. E. Matusov, N. Ueffing, and H. Ney. 2006. Computing consensus translation from multiple machine translation systems using enhanced hypotheses alignment. In EACL, Trento, Italy.
22. R. C. Moore. 2005. A discriminative framework for bilingual word alignment. In EMNLP, Vancouver, Canada.
23. F. Och and H. Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1):19 - 51. (Pubitemid 37049767)
24. F. Och and H. Ney. 2004. The alignment template approach to statistical machine translation. Computational Linguistics, 30(4):417 - 449. (Pubitemid 41399543)
25. F. Och. 2003. Minimum error rate training in statistical machine translation. In ACL, Sapporo, Japan.
26. P. Resnik, M. Olsen, and M. Diab. 1997. Creating a parallel corpus from the book of 2000 tongues. In Text Encoding Initiative 10th Anniversary User Conference, Providence, RI, USA.
27. C. Schafer and D. Yarowsky. 2002. Inducing translation lexicons via diverse similarity measures and bridge languages. In CoNLL, Taipei, Taiwan.
28. K. C. Sim, W. J. Byrne, M. J. F. Gales, H. Sahbi, and P. C. Woodland. 2007. Consensus network decoding for statistical machine translation system combination. In IEEE International Conference on Acoustics, Speech, and Signal Processing, Honolulu, HI, USA.
29. M. Simard. 1999. Text translation alignment: Three languages are better than two. In EMNLP-VLC, College Park, MD, USA.
30. N. Ueffing and H. Ney. 2005. Word-level confidence estimation for machine translation using phrase-based translation models. In EMNLP, pages 763 - 770, Vancouver, Canada.
31. UN, 2006. ODS UN Parallel Corpus. http://ods.un.org/.
32. S. Vogel, H. Ney, and C. Tillmann. 1996. HMM based word alignment in statistical translation. In COLING, pages 836-841, Copenhagen, Denmark.