The best lexical metric for phrase-based statistical MT system optimization

NAACL HLT 2010 - Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Proceedings of the Main Conference

Volumn , Issue , 2010, Pages 555-563

  Cer, Daniel ^a   Manning, Christopher D ^a   Jurafsky, Daniel ^a  

^a STANFORD UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

AUTOMATIC EVALUATION; BEST CHOICE; EDIT DISTANCE; GOOD CORRELATIONS; HUMAN JUDGMENTS; PARAMETERIZATIONS; SOURCE LANGUAGE; SYSTEM OPTIMIZATIONS; TRANSLATION SYSTEMS;

COMPUTATIONAL LINGUISTICS;

OPTIMIZATION;

EID: 84858389198     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (30)

1. Abhaya Agarwal and Alon Lavie. 2008. METEOR, M-BLEU and M-TER: Evaluation metrics for high-correlation with human rankings of machine translation output. In StatMT workshop at ACL.
2. Chris Callison-Burch, Miles Osborne, and Philipp Koehn. 2006. Re-evaluating the role of BLEU in machine translation research. In EACL.
3. Chris Callison-Burch. 2009. Fast, cheap, and creative: Evaluating translation quality using Amazon's Mechanical Turk. In EMNLP.
4. Daniel Cer, Michel Galley, Christopher D. Manning, and Dan Jurafsky. 2010. Phrasal: A statistical machine translation toolkit for exploring new model features. In NAACL.
5. Pi-Chuan Chang, Michel Galley, and Christopher D. Manning. 2008. Optimizing chinese word segmentation for machine translation performance. In StatMT workshop at ACL.
6. David Chiang, Yuval Marton, and Philip Resnik. 2008. Online large-margin training of syntactic and structural translation features. In EMNLP.
7. David Chiang, Kevin Knight, and Wei Wang. 2009. 11,001 new features for statistical machine translation. In NAACL.
8. Koby Crammer and Yoram Singer. 2003. Ultraconservative online algorithms for multiclass problems. JMLR, 3:951-991.
9. George Doddington. 2002. Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In HLT.
10. Michel Galley and Christopher D. Manning. 2008. A simple and effective hierarchical phrase reordering model. In EMNLP.
11. Michel Galley, Jonathan Graehl, Kevin Knight, Daniel Marcu, Steve DeNeefe, Wei Wang, and Ignacio Thayer. 2006. Scalable inference and training of context-rich syntactic translation models. In ACL.
12. Michel Galley, Spence Green, Daniel Cer, Pi-Chuan Chang, and Christopher D. Manning. 2009. Stanford university's arabic-to-english statistical machine translation system for the 2009 NIST evaluation. In NIST Open Machine Translation Evaluation Meeting.
13. Philipp Koehn, Franz Josef Och, and Daniel Marcu. 2003. Statistical phrase-based translation. In NAACL.
14. Philipp Koehn, Hieu Hoang, Alexandra Birch, Chris Callison-Burch, Marcello Federico, Nicola Bertoldi, Brooke Cowan, Wade Shen, Christine Moran, Richard Zens, Chris Dyer, Ondrej Bojar, Alexandra Constantin, and Evan Herbst. 2007. Moses: Open source toolkit for statistical machine translation. In ACL.
15. Alon Lavie and Michael J. Denkowski. 2009. The METEOR metric for automatic evaluation of machine translation. Machine Translation, 23.
16. Percy Liang, Ben Taskar, and Dan Klein. 2006. Alignment by agreement. In NAACL.
17. Lucian Vlad Lita, Abe Ittycheriah, Salim Roukos, and Nanda Kambhatla. 2003. tRuEcasIng. In ACL.
18. Bonnie Dorr Matthew Snover, Nitin Madnani and Richard Schwartz. 2008. TERp system description. In MetricsMATR workshop at AMTA.
19. Sonja Nießen, Franz Josef Och, and Hermann Ney. 2000. An evaluation tool for machine translation: Fast evaluation for MT research. In LREC.
20. Franz Josef Och and Hermann Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1):19-51. (Pubitemid 37049767)
21. Franz Josef Och. 2003. Minimum error rate training in statistical machine translation. In ACL.
22. Kishore Papineni, Salim Roukos, Todd Ward, and Wei-Jing Zhu. 2002. BLEU: a method for automatic evaluation of machine translation. In ACL.
23. M. Przybocki, K. Peterson, and S. Bronsart. 2008. Official results of the "Metrics for MAchine TRanslation" Challenge (MetricsMATR08). Technical report, NIST, http://nist.gov/speech/tests/metricsmatr/2008/results/.
24. Matthew Snover, Bonnie Dorr, Richard Schwartz, Linnea Micciulla, and John Makhoul. 2006. A study of translation edit rate with targeted human annotation. In AMTA.
25. Matthew Snover, Nitin Madnani, Bonnie J. Dorr, and Richard Schwartz. 2009. Fluency, adequacy, or HTER?: exploring different human judgments with a tunable MT metric. In StatMT workshop at EACL).
26. Rion Snow, Brendan O'Connor, Daniel Jurafsky, and Andrew Ng. 2008. Cheap and fast - but is it good? Evaluating non-expert annotations for natural language tasks. In EMNLP.
27. Andreas Stolcke. 2002. SRILM - an extensible language modeling toolkit. In ICSLP.
28. Huihsin Tseng, Pichuan Chang, Galen Andrew, Daniel Jurafsky, and Christopher D. Manning. 2005. A conditional random field word segmenter. In SIGHAN.
29. Taro Watanabe, Jun Suzuki, Hajime Tsukada, and Hideki Isozaki. 2007. Online large-margin training for statistical machine translation. In EMNLP-CoNLL.
30. Omar F. Zaidan and Chris Callison-Burch. 2009. Feasibility of human-in-the-loop minimum error rate training. In EMNLP, pages 52-61, August.