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Mining Parallel Resources for Machine Translation from Comparable Corpora

  • Conference paper
Computational Linguistics and Intelligent Text Processing (CICLing 2015)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 9041))

Abstract

Good performance of Statistical Machine Translation (SMT) is usually achieved with huge parallel bilingual training corpora, because the translations of words or phrases are computed basing on bilingual data. However, in case of low-resource language pairs such as English-Bengali, the performance is affected by insufficient amount of bilingual training data. Recently, comparable corpora became widely considered as valuable resources for machine translation. Though very few cases of sub-sentential level parallelism are found between two comparable documents, there are still potential parallel phrases in comparable corpora. Mining parallel data from comparable corpora is a promising approach to collect more parallel training data for SMT. In this paper, we propose an automatic alignment of English-Bengali comparable sentences from comparable documents. We use a novel textual entailment method and distributional semantics for text similarity. Subsequently, we apply template-based phrase extraction technique to aligned parallel phrases from comparable sentence pairs. The effectiveness of our approach is demonstrated by using parallel phrases as additional training examples for an English-Bengali phrase-based SMT system. Our system achieves significant improvement in terms of translation quality over the baseline system.

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References

  1. Agirre, E., Baneab, C., Cardiec, C., Cerd, D., Diabe, M., Gonzalez-Agirrea, A., Guof, W., Mihalcea, R., Rigau, G., Wiebeg, J.: Semeval-2014 task 10: Multilingual semantic textual similarity. In: Proceedings of SemEval 2014, p. 81 (2014)

    Google Scholar 

  2. Alonso-Rorís, V.M., Gago, J.M.S., Rodríguez, R.P., Costa, C.R., Carballa, M.A.G., Rifón, L.A.: Information Extraction in Semantic, Highly-Structured, and Semi-Structured Web Sources. Polibits 49, 69–75 (2014)

    Google Scholar 

  3. Blei, D., Ng, A., Jordan, M.: Latent Dirichlet Allocation. The Journal of Machine Learning Research 3, 993–1022 (2003)

    MATH  Google Scholar 

  4. Chaney, A.J., Blei, D.M.: Visualizing topic models. In: International AAAI Conference on Social Media and Weblogs. Department of Computer Science, Princeton University Princeton, NJ, USA (March 2012)

    Google Scholar 

  5. Chiao, Y.-C., Zweigenbaum, P.: Looking for candidate translational equivalents in specialized, comparable corpora. In: Proceedings of the 19th International Conference on Computational Linguistics, vol. 2, pp. 1–5. Association for Computational Linguistics (2002)

    Google Scholar 

  6. Dagan, I., Glickman, O.: Probabilistic textual entailment: Generic applied modeling of language variability. In: Proceedings of PASCAL Workshop on Learning Methods for Text Understanding and Mining, p. 6. Grenoble (2004)

    Google Scholar 

  7. Das, N., Ghosh, S., Gonçalves, T., Quaresma, P.: Comparison of Different Graph Distance Metrics for Semantic Text Based Classification. Polibits 49, 51–57 (2014)

    Google Scholar 

  8. Déjean, H., Gaussier, É., Sadat, F.: Bilingual terminology extraction: an approach based on a multilingual thesaurus applicable to comparable corpora. In: Proceedings of the 19th International Conference on Computational Linguistics COLING, pp. 218–224 (2002)

    Google Scholar 

  9. Doddington, G.: Automatic evaluation of machine translation quality using n-gram co-occurrence statistics. In: Proceedings of the Second International Conference on Human Language Technology Research, pp. 138–145. Morgan Kaufmann Publishers Inc. (2002)

    Google Scholar 

  10. Fung, P., McKeown, K.: Finding terminology translations from non-parallel corpora. In: Proceedings of the 5th Annual Workshop on Very Large Corpora, pp. 192–202 (1997)

    Google Scholar 

  11. Fung, P., Yee, L.Y.: An IR approach for translating new words from nonparallel, comparable texts. In: Proceedings of the 17th International Conference on Computational Linguistics, pp. 414–420. Association for Computational Linguistics (1998)

    Google Scholar 

  12. Gupta, R., Pal, S., Bandyopadhyay, S.: Improving MT System Using Extracted Parallel Fragments of Text from Comparable Corpora. In: Proceedings of 6th Workshop of Building and Using Comparable Corpora (BUCC), pp. 69–76. ACL, Sofia (2013)

    Google Scholar 

  13. Cicekli, I., Guvenir, H.A.: Learning Translation Templates from Bilingual Translation Examples. Applied Intelligence 15(1), 57–76 (2001)

    Article  MATH  Google Scholar 

  14. Kneser, R., Ney, H.: Improved backing-off for n-gram language modeling. In: Proceedings of the IEEE International Conference on Acoustics, Speech and Signal Processing, vol. I, pp. 181–184 (1995)

    Google Scholar 

  15. Koehn, P., Och, F.J., Marcu, D.: 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, pp. 48–54. Association for Computational Linguistics (2003)

    Google Scholar 

  16. Mikolov, T., Sutskever, I., Chen, K., Corrado, G.S., Dean, J.: Distribute Representations of Words and Phrases and their Compositionality. In: Burges, C., Bottou, L., Welling, M., Ghahramani, Z., Weinberger, K. (eds.) Advances in Neural Information Processing Systems 26, pp. 3111–3119. Curran Associates, Inc. (2013)

    Google Scholar 

  17. Otero, P.G.: Learning bilingual lexicons from comparable english and spanish corpora. In: Proceedings of MT Summit xI, pp. 191–198 (2007)

    Google Scholar 

  18. Papineni, K., Roukos, S., Ward, T., Zhu, W.-J.: BLEU: a method for automatic evaluation of machine translation. In: Proceedings of the 40th Annual Meeting on Association for Computational Linguistics, pp. 311–318. Association for Computational Linguistics (2002)

    Google Scholar 

  19. Pakray, P., Sojka, P.: An Architecture for Scientific Document Retrieval Using Textual and Math Entailment Modules. In: RASLAN 2014: Recent Advances in Slavonic Natural Language Processing, Karlova Studánka, Czech Republic, December 5-7 (2014)

    Google Scholar 

  20. Rapp, R.: Automatic identification of word translations from unrelated English and German corpora. In: Proceedings of the 37th Annual Meeting of the Association for Computational Linguistics on Computational Linguistics, pp. 519–526. Association for Computational Linguistics (1999)

    Google Scholar 

  21. Rehurek, R., Sojka, P.: Software Framework for Topic Modelling with Large Corpora. In: Proceedings of LREC 2010 Workshop New Challenges for NLP Frameworks, pp. 45–50. ELRA, Valletta (2010)

    Google Scholar 

  22. Pal, S., Pakray, P., Naskar, S.K.: Automatic Building and Using Parallel Resources for SMT from Comparable Corpora. In: Proceedings of the 3rd Workshop on Hybrid Approaches to Translation (HyTra) @ EACL 2014, April 27, pp. 47–56. ssociation for Computational Linguistics, Gothenburg (2014)

    Google Scholar 

  23. Saralegui, X., San Vicente, I., Gurrutxaga, A.: Automatic generation of bilingual lexicons from comparable corpora in a popular science domain. In: LREC 2008 Workshop on Building and Using Comparable Corpora (2008)

    Google Scholar 

  24. Sidorov, G.: Should syntactic n-grams contain names of syntactic relations? International Journal of Computational Linguistics and Applications 5(1), 139–158 (2014)

    MathSciNet  Google Scholar 

  25. Smith, J.R., Quirk, C., Toutanova, K.: Extracting parallel sentence from comparable corpora using document level alignment. In: Human Language Technologies: The 2010 Annual Conference of the North American Chapter of the Association for Computational Linguistics, pp. 403–411. Association for Computational Linguistics (2010)

    Google Scholar 

  26. Snover, M., Dorr, B., Schwartz, R., Micciulla, L., Makhoul, J.: A study of translation edit rate with targeted human annotation. In: Proceedings of Association for Machine Translation in the Americas, Cambridge, Massachusetts, USA, pp. 223–231 (2006)

    Google Scholar 

  27. Stolcke, A.: SRILM-an extensible language modeling toolkit. In: Proceedings of the International Conference on Spoken Language Processing, vol. 2, pp. 901–904 (2002)

    Google Scholar 

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Author information

Authors and Affiliations

  1. Universität Des Saarlandes, Saarbrucken, Germany

    Santanu Pal & Josef van Genabith

  2. National Institute of Technology, Mizoram, India

    Partha Pakray

  3. Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico City, Mexico

    Alexander Gelbukh

Authors
  1. Santanu Pal
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  2. Partha Pakray
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  3. Alexander Gelbukh
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  4. Josef van Genabith
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Corresponding author

Correspondence to Santanu Pal .

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Editors and Affiliations

  1. Centro de Investigación en Computación, Instituto Politécnico Nacional, Mexico DF, Mexico

    Alexander Gelbukh

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© 2015 Springer International Publishing Switzerland

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Pal, S., Pakray, P., Gelbukh, A., van Genabith, J. (2015). Mining Parallel Resources for Machine Translation from Comparable Corpora. In: Gelbukh, A. (eds) Computational Linguistics and Intelligent Text Processing. CICLing 2015. Lecture Notes in Computer Science(), vol 9041. Springer, Cham. https://doi.org/10.1007/978-3-319-18111-0_40

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  • DOI: https://doi.org/10.1007/978-3-319-18111-0_40

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-18110-3

  • Online ISBN: 978-3-319-18111-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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