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Learning Curve with Machine Translation Based on Parallel, Bilingual Corpora

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Machine Intelligence and Big Data in Industry

Part of the book series: Studies in Big Data ((SBD,volume 19))

Abstract

Machine Translation is a branch of computer science that automatically handles translation of a text from a source language to a target language. This article summarizes the experience gained during UKSW project, part of which deals with translation of legal phrases between English and Polish. The article describes consecutive steps of the project, i.e. collecting data and creating parallel, bilingual corpora, checking open source ready-made solutions and the novel, effective SMT solution that has been proposed. The final chapter summarizes the solution, together with the results based on BLEU metrics.

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Notes

  1. 1.

    http://translate.google.pl.

  2. 2.

    http://duolingo.com.

  3. 3.

    http://joshua-decoder.org/6.0/pipeline.html.

  4. 4.

    https://github.com/jladcr/Moses-for-Mere-Mortals.

  5. 5.

    http://www.statmt.org/europarl/.

  6. 6.

    http://www.ted.com/talks/browse.

  7. 7.

    http://pelcra.pl/new/.

  8. 8.

    http://www.slowniki.org.pl/.

  9. 9.

    http://www.diki.pl/.

  10. 10.

    http://opus.lingfil.uu.se/index.php.

  11. 11.

    http://eur-lex.europa.eu/.

  12. 12.

    http://curia.europa.eu/.

  13. 13.

    https://lucene.apache.org.

  14. 14.

    http://www.statmt.org/moses/?n=FactoredTraining.RunGIZA.

  15. 15.

    https://code.google.com/p/berkeleyaligner/.

  16. 16.

    https://github.com/danielvarga/hunalign.

  17. 17.

    http://morfologik.blogspot.com.

References

  1. Bond, F.: Machine translation introduction - lecture 1. NTT Communication Science Laboratories (2006)

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  2. Arnold, D.J., Balkan, L., Meijer, S., Humphreys, R.L., Sadler, L.: Machine Translation: An Introductory Guide. Blackwells-NCC, London (1994)

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  3. 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 of the Association for Computational Linguistics (ACL), Philadelphia, pp. 311–318 (2002)

    Google Scholar 

  4. Koehn, P.: Europarl: a parallel corpus for statistical machine translation. In: MT Summit, vol. 5, pp. 79–86 (2005)

    Google Scholar 

  5. Machado, J.M., Hilario, L.F.: Moses for Mere Mortals. Tutorial. A machine translation chain for the real world (2014). https://github.com/jladcr/Moses-for-Mere-Mortals/blob/master/Tutorial.pdf

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Author information

Authors and Affiliations

  1. National Information Processing Institute, al. Niepodleglosci. 188B, 00-608, Warsaw, Poland

    Maciej Kowalski

Authors
  1. Maciej Kowalski
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Correspondence to Maciej Kowalski .

Editor information

Editors and Affiliations

  1. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Dominik Ryżko

  2. Institute of Computer Science, Warsaw University of Technology, Abo, Poland

    Piotr Gawrysiak

  3. Institute of Computer Science, Warsaw University of Technology, Warszawa, Poland

    Marzena Kryszkiewicz

  4. Institute of Computer Science, Warsaw University of Technology, Warsaw, Poland

    Henryk Rybiński

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Kowalski, M. (2016). Learning Curve with Machine Translation Based on Parallel, Bilingual Corpora. In: Ryżko, D., Gawrysiak, P., Kryszkiewicz, M., Rybiński, H. (eds) Machine Intelligence and Big Data in Industry. Studies in Big Data, vol 19. Springer, Cham. https://doi.org/10.1007/978-3-319-30315-4_2

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  • DOI: https://doi.org/10.1007/978-3-319-30315-4_2

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-30314-7

  • Online ISBN: 978-3-319-30315-4

  • eBook Packages: EngineeringEngineering (R0)

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