A systematic exploration of diversity in machine translation

EMNLP 2013 - 2013 Conference on Empirical Methods in Natural Language Processing, Proceedings of the Conference

Volumn , Issue , 2013, Pages 1100-1111

  Gimpel, Kevin ^a   Batra, Dhruv ^b   Dyer, Chris ^c   Shakhnarovich, Gregory ^a  

^a TOYOTA TECHNOLOGICAL INSTITUTE AT CHICAGO   (United States)

^b VIRGINIA POLYTECHNIC INSTITUTE AND STATE UNIVERSITY   (United States)

^c CARNEGIE MELLON UNIVERSITY   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

COMPUTATIONAL LINGUISTICS; COMPUTER AIDED LANGUAGE TRANSLATION;

DISCRIMINATIVE RERANKING; IMPROVE PERFORMANCE; MACHINE TRANSLATIONS; POST-EDITING; RICH FEATURES; STATISTICAL MACHINE TRANSLATION; SYSTEM COMBINATION; SYSTEMATIC EXPLORATION;

NATURAL LANGUAGE PROCESSING SYSTEMS;

EID: 84926335585     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

References (63)

1. N. Bach, F. Huang, and Y. Al-Onaizan. 2011. Goodness: A method for measuring machine translation confidence. In Proc. of ACL.
2. D. Batra, P. Yadollahpour, A. Guzman-Rivera, and G Shakhnarovich. 2012. Diverse M-best solutions in Markov random fields. In Proc. of ECCV.
3. O. Bojar, C. Buck, C. Callison-Burch, C. Federmann, B. Haddow, P. Koehn, C. Monz, M. Post, R. Soricut, and L. Specia. 2013. Findings of the 2013 Workshop on Statistical Machine Translation. In Proc. of WMT.
4. P. F Brown, P. V. de Souza, R. L. Mercer, V. J. Della Pietra, and J. C. Lai. 1992. Class-based N-gram models of natural language. Computational Linguistics, 18.
5. C. Callison-Burch, P. Koehn, C. Monz, and O. Zaidan. 2011. Findings of the 2011 Workshop on Statistical Machine Translation. In Proc. of WMT.
6. C. Callison-Burch, P. Koehn, C. Monz, M. Post, R. Soricut, and L. Specia. 2012. Findings of the 2012 Workshop on Statistical Machine Translation. In Proc. of WMT.
7. D. Cer, C. D. Manning, and D. Jurafsky. 2013. Positive diversity tuning for machine translation system combination. In Proc. of WMT.
8. P. Chang, M. Galley, and C. D. Manning. 2008. Optimizing Chinese word segmentation for machine translation performance. In Proc. of WMT.
9. E. Charniak and M. Johnson. 2005. Coarse-to-fine n-best parsing and maxent discriminative reranking. In Proc. of ACL.
10. S. Chatterjee and N. Cancedda. 2010. Minimum error rate training by sampling the translation lattice. In Proc. of EMNLP.
11. S. Chen and J. Goodman. 1998. An empirical study of smoothing techniques for language modeling. Technical report 10-98, Harvard University.
12. D. Chiang. 2007. Hierarchical phrase-based translation. Computational Linguistics, 33(2).
13. M. Collins and T. Koo. 2005. Discriminative reranking for natural language parsing. Computational Linguistics, 31(1).
14. M. Collins. 2000. Discriminative reranking for natural language parsing. In Proc. of ICML.
15. J. DeNero, D. Chiang, and K. Knight. 2009. Fast consensus decoding over translation forests. In Proc. of ACL.
16. J. Devlin and S. Matsoukas. 2012. Trait-based hypothesis selection for machine translation. In Proc. of NAACL.
17. C. Dyer. 2009. Using a maximum entropy model to build segmentation lattices for MT. In Proc. of HLT-NAACL.
18. C. Dyer. 2010. A Formal Model of Ambiguity and its Applications in Machine Translation. Ph.D. thesis, University of Maryland.
19. J. R. Finkel, C. D. Manning, and A. Y. Ng. 2006. Solving the problem of cascading errors: Approximate Bayesian inference for linguistic annotation pipelines. In Proc. of EMNLP.
20. E. M. Gertz and S. J. Wright. 2003. Object-oriented software for quadratic programming. ACM Transactions on Mathematical Software, 29(1).
21. J. Gillenwater, A. Kulesza, and B. Taskar. 2012. Discovering diverse and salient threads in document collections. In Proc. of EMNLP.
22. K. Heafield and A. Lavie. 2010a. Combining machine translation output with open source: The Carnegie Mellon multi-engine machine translation scheme. The Prague Bulletin of Mathematical Linguistics, 93.
23. K. Heafield and A. Lavie. 2010b. Voting on n-grams for machine translation system combination. In Proc. of AMTA.
24. K. Heafield. 2011. Kenlm: Faster and smaller language model queries. In Proc. of WMT.
25. A. Hildebrand and S. Vogel. 2008. Combination of machine translation systems via hypothesis selection from combined n-best lists. In Proc. of AMTA.
26. H. Hoang, P. Koehn, and A. Lopez. 2009. A Unified Framework for Phrase-Based, Hierarchical, and Syntax-Based Statistical Machine Translation. In Proc. of IWSLT.
27. M. Hopkins and J. May. 2011. Tuning as ranking. In Proc. of EMNLP.
28. L. Huang. 2008. Forest reranking: Discriminative parsing with non-local features. In Proc. of ACL.
29. T. Joachims, T. Finley, and C. Yu. 2009. Cuttingplane training of structural SVMs. Machine Learning, 77(1).
30. P. Koehn, F. J. Och, and D. Marcu. 2003. Statistical phrase-based translation. In Proc. of HLT-NAACL.
31. P. Koehn, H. Hoang, A. Birch, C. Callison-Burch, M. Federico, N. Bertoldi, B. Cowan, W. Shen, C. Moran, R. Zens, C. Dyer, O. Bojar, A. Constantin, and E. Herbst. 2007. Moses: Open source toolkit for statistical machine translation. In Proc. of ACL (demo session).
32. P. Koehn. 2010. Enabling monolingual translators: Postediting vs. options. In Proc. of NAACL.
33. M. Koponen. 2012. Comparing human perceptions of post-editing effort with post-editing operations. In Proc. of WMT.
34. A. Kulesza and B. Taskar. 2010. Structured determinan-tal point processes. In Proc. of NIPS.
35. A. Kulesza and B. Taskar. 2011. Learning determinantal point processes. In Proc. of UAI.
36. S. Kumar and W. Byrne. 2004. Minimum bayes-risk decoding for statistical machine translation. In Proc. of HLT-NAACL.
37. S. Kumar, W. Macherey, C. Dyer, and F. Och. 2009. Efficient minimum error rate training and minimum Bayes-risk decoding for translation hypergraphs and lattices. In Proc. of ACL-IJCNLP.
38. Y. Lee, K. Papineni, S. Roukos, O. Emam, and H. Hassan. 2003. Language model based Arabic word segmentation. In Proc. of ACL.
39. Z. Li, J. Eisner, and S. Khudanpur. 2009. Variational decoding for statistical machine translation. In Proc. of ACL.
40. P. Liang. 2005. Semi-supervised learning for natural language. Master's thesis, Massachusetts Institute of Technology.
41. C. Lin and F. J. Och. 2004. Orange: a method for evaluating automatic evaluation metrics for machine translation. In Proc. of COLING.
42. W. Macherey and F. J. Och. 2007. An empirical study on computing consensus translations from multiple machine translation systems. In Proc. of EMNLP-CoNLL.
43. W. Macherey, F. J. Och, I. Thayer, and J. Uszkoreit. 2008. Lattice-based minimum error rate training for statistical machine translation. In Proc. of EMNLP.
44. F. J. Och and H. Ney. 2002. Discriminative training and maximum entropy models for statistical machine translation. In Proc. of ACL.
45. F. J. Och and H. Ney. 2003. A systematic comparison of various statistical alignment models. Computational Linguistics, 29(1).
46. F. J. Och, D. Gildea, S. Khudanpur, A. Sarkar, K. Yamada, A. Fraser, S. Kumar, L. Shen, D. Smith, K. Eng, V. Jain, Z. Jin, and D. Radev. 2004. A smorgasbord of features for statistical machine translation. In HLT-NAACL.
47. F. J. Och. 2003. Minimum error rate training for statistical machine translation. In Proc. of ACL.
48. K. Papineni, S. Roukos, T. Ward, and W.J. Zhu. 2002. BLEU: a method for automatic evaluation of machine translation. In Proc. of ACL.
49. A. Pauls and D. Klein. 2012. Large-scale syntactic language modeling with treelets. In Proc. of ACL.
50. A.-V. Rosti, N. F. Ayan, B. Xiang, S. Matsoukas, R. Schwartz, and B. Dorr. 2007. Combining outputs from multiple machine translation systems. In HLT-NAACL.
51. L. Shen and A. K. Joshi. 2003. An SVM-based voting algorithm with application to parse reranking. In Proc. of CoNLL.
52. L. Shen, A. Sarkar, and F. J. Och. 2004. Discriminative reranking for machine translation. In Proc. of HLT-NAACL.
53. L. Specia, N. Hajlaoui, C. Hallett, and W. Aziz. 2011. Predicting machine translation adequacy. In Proc. of MT Summit XIII.
54. L. Specia. 2011. Exploiting objective annotations for measuring translation post-editing effort. In Proc. of EAMT.
55. A. Stolcke. 2002. SRILM - an extensible language modeling toolkit. In Proc. of ICSLP.
56. M. Tatsumi. 2009. Correlation between automatic evaluation metric scores, post-editing speed, and some other factors. In Proc. of MT Summit XII.
57. K. Toutanova, D. Klein, C. D. Manning, and Y. Singer. 2003. Feature-rich part-of-speech tagging with a cyclic dependency network. In Proc. of HLT-NAACL.
58. R. Tromble, S. Kumar, F. J. Och, and W. Macherey. 2008. Lattice Minimum Bayes-Risk decoding for statistical machine translation. In Proc. of EMNLP.
59. I. Tsochantaridis, T. Joachims, T. Hofmann, and Y. Altun. 2005. Large margin methods for structured and interdependent output variables. JMLR, 6.
60. A. Venugopal, A. Zollmann, N.A. Smith, and S. Vogel. 2008. Wider pipelines: N-best alignments and parses in MT training. In Proc. of AMTA.
61. I. H. Witten and T. C. Bell. 1991. The zero-frequency problem: Estimating the probabilities of novel events in adaptive text compression. IEEE Transactions on Information Theory, 37(4).
62. T. Xiao, J. Zhu, and T. Liu. 2013. Bagging and boosting statistical machine translation systems. Artif. Intell., 195.
63. P. Yadollahpour, D. Batra, and G. Shakhnarovich. 2013. Discriminative re-ranking of diverse segmentations. In Proc. of CVPR.