Online Learning via Dynamic Reranking for Computer Assisted Translation

  • Pascual Martínez-Gómez
  • Germán Sanchis-Trilles
  • Francisco Casacuberta
Part of the Lecture Notes in Computer Science book series (LNCS, volume 6609)


New techniques for online adaptation in computer assisted translation are explored and compared to previously existing approaches. Under the online adaptation paradigm, the translation system needs to adapt itself to real-world changing scenarios, where training and tuning may only take place once, when the system is set-up for the first time. For this purpose, post-edit information, as described by a given quality measure, is used as valuable feedback within a dynamic reranking algorithm. Two possible approaches are presented and evaluated. The first one relies on the well-known perceptron algorithm, whereas the second one is a novel approach using the Ridge regression in order to compute the optimum scaling factors within a state-of-the-art SMT system. Experimental results show that such algorithms are able to improve translation quality by learning from the errors produced by the system on a sentence-by-sentence basis.


Online Learning Machine Translation Ridge Regression Statistical Machine Translation Language Pair 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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  1. 1.
    Brown, P., Pietra, S.D., Pietra, V.D., Mercer, R.: The mathematics of machine translation. In: Computational Linguistics, vol. 19, pp. 263–311 (1993)Google Scholar
  2. 2.
    Zens, R., Och, F.J., Ney, H.: Phrase-based statistical machine translation. In: Jarke, M., Koehler, J., Lakemeyer, G. (eds.) KI 2002. LNCS (LNAI), vol. 2479, pp. 18–32. Springer, Heidelberg (2002)CrossRefGoogle Scholar
  3. 3.
    Koehn, P., Och, F.J., Marcu, D.: Statistical phrase-based translation. In: Proc. HLT/NAACL 2003, pp. 48–54 (2003)Google Scholar
  4. 4.
    Callison-Burch, C., Fordyce, C., Koehn, P., Monz, C., Schroeder, J.: (meta-) evaluation of machine translation. In: Proc. of the Workshop on SMT. ACL, pp. 136–158 (2007)Google Scholar
  5. 5.
    Papineni, K., Roukos, S., Ward, T.: Maximum likelihood and discriminative training of direct translation models. In: Proc. of ICASSP 1988, pp. 189–192 (1998)Google Scholar
  6. 6.
    Och, F., Ney, H.: Discriminative training and maximum entropy models for statistical machine translation. In: Proc. of the ACL 2002, pp. 295–302 (2002)Google Scholar
  7. 7.
    Och, F., Zens, R., Ney, H.: Efficient search for interactive statistical machine translation. In: Proc. of EACL 2003, pp. 387–393 (2003)Google Scholar
  8. 8.
    Sanchis-Trilles, G., Casacuberta, F.: Log-linear weight optimisation via bayesian adaptation in statistical machine translation. In: Proceedings of COLING 2010, Beijing, China (2010)Google Scholar
  9. 9.
    Callison-Burch, C., Bannard, C., Schroeder, J.: Improving statistical translation through editing. In: Proc. of 9th EAMT Workshop Broadening Horizons of Machine Translation and its Applications, Malta (2004)Google Scholar
  10. 10.
    Barrachina, S., et al.: Statistical approaches to computer-assisted translation. Computational Linguistics 35, 3–28 (2009)CrossRefGoogle Scholar
  11. 11.
    Casacuberta, F., et al.: Human interaction for high quality machine translation. Communications of the ACM 52, 135–138 (2009)CrossRefGoogle Scholar
  12. 12.
    Ortiz-Martínez, D., García-Varea, I., Casacuberta, F.: Online learning for interactive statistical machine translation. In: Proceedings of NAACL HLT, Los Angeles (2010)Google Scholar
  13. 13.
    España-Bonet, C., Màrquez, L.: Robust estimation of feature weights in statistical machine translation. In: 14th Annual Conference of the EAMT (2010)Google Scholar
  14. 14.
    Reverberi, G., Szedmak, S., Cesa-Bianchi, N., et al.: Deliverable of package 4: Online learning algorithms for computer-assisted translation (2008)Google Scholar
  15. 15.
    Crammer, K., Dekel, O., Keshet, J., Shalev-Shwartz, S., Singer, Y.: Online passive-aggressive algorithms. Journal of Machine Learning Research 7, 551–585 (2006)zbMATHGoogle Scholar
  16. 16.
    Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proc. of AMTA, Cambridge, MA, USA (2006)Google Scholar
  17. 17.
    Papineni, K., Roukos, S., Ward, T., Zhu, W.: Bleu: A method for automatic evaluation of machine translation. In: Proc. of ACL 2002 (2002)Google Scholar
  18. 18.
    Rosenblatt, F.: The perceptron: A probabilistic model for information storage and organization in the brain. Psychological Review 65, 386–408 (1958)CrossRefGoogle Scholar
  19. 19.
    Collins, M.: Discriminative training methods for hidden markov models: Theory and experiments with perceptron algorithms. In: EMNLP 2002, Philadelphia, PA, USA, pp. 1–8 (2002)Google Scholar
  20. 20.
    Koehn, P.: Europarl: A parallel corpus for statistical machine translation. In: Proc. of the MT Summit X, pp. 79–86 (2005)Google Scholar
  21. 21.
    Koehn, P., et al.: Moses: Open source toolkit for statistical machine translation. In: Proc. of the ACL Demo and Poster Sessions, Prague, Czech Republic, pp. 177–180 (2007)Google Scholar
  22. 22.
    Och, F.: Minimum error rate training for statistical machine translation. In: Proc. of ACL 2003, pp. 160–167 (2003)Google Scholar
  23. 23.
    Kneser, R., Ney, H.: Improved backing-off for m-gram language modeling. In: IEEE Int. Conf. on Acoustics, Speech and Signal Processing II, pp. 181–184 (1995)Google Scholar
  24. 24.
    Stolcke, A.: SRILM – an extensible language modeling toolkit. In: Proc. of ICSLP 2002, pp. 901–904 (2002)Google Scholar

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© Springer-Verlag Berlin Heidelberg 2011

Authors and Affiliations

  • Pascual Martínez-Gómez
    • 1
  • Germán Sanchis-Trilles
    • 1
  • Francisco Casacuberta
    • 1
  1. 1.Instituto Tecnológico de InformáticaUniversidad Politécnica de ValenciaSpain

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