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Digging Language Model – Maximum Entropy Phrase Extraction

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Text, Speech, and Dialogue (TSD 2016)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 9924))

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Abstract

This work introduces our maximum entropy phrase extraction method for the Czech – English translation task. Two different corpora and language models of the different sizes were used to explore a potential of the maximum entropy phrase extraction method and phrase table content optimization. Additionally, two different maximum entropy estimation criteria were compared with the state of the art phrase extraction method too. In the case of a domain oriented translation, maximum entropy phrase extraction significantly improves translation precision.

This work was supported by the project LO1506 of the Czech Ministry of Education, Youth and Sports. Access to computing and storage facilities owned by parties and projects contributing to the National Grid Infrastructure MetaCentrum, provided under the programme “Projects of Large Research, Development, and Innovations Infrastructures” (CESNET LM2015042), is greatly appreciated.

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Notes

  1. 1.

    http://ufal.mff.cuni.cz/czeng/.

  2. 2.

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

  3. 3.

    http://www.statmt.org/moses/.

  4. 4.

    https://kheafield.com/code/kenlm/.

  5. 5.

    There is a perplexity reduction for the EuCsEn corpus too, but is only 3.5 % relatively in opposite to the 18 % relative reduction for the CzEng corpus.

References

  1. Kanis, J., Müller, L.: Advances in czech – signed speech translation. In: Matoušek, V., Mautner, P. (eds.) TSD 2009. LNCS, vol. 5729, pp. 48–55. Springer, Heidelberg (2009)

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  2. Lavecchia, C., Langlois, D., Smaïli, K.: Phrase-based machine translation based on simulated annealing. In: Proceedings of the LREC, Marrakech, Morocco. ELRA (2008)

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  3. Koehn, P., Och, F.J., Marcu, D.: Statistical phrase-based translation. In: HLT/NAACL (2003)

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  4. Venugopal, A., Vogel, S., Waibel, A.: Effective phrase translation extraction from alignment models. In: Proceedings of the ACL, pp. 319–326 (2003)

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Author information

Authors and Affiliations

  1. Faculty of Applied Sciences, NTIS – New Technologies for the Information Society, University of West Bohemia, Univerzitní 8, 306 14, Pilsen, Czech Republic

    Jakub Kanis

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  1. Jakub Kanis
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Correspondence to Jakub Kanis .

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Editors and Affiliations

  1. Masaryk University , Brno, Czech Republic

    Petr Sojka

  2. Masaryk University , Brno, Czech Republic

    Aleš Horák

  3. Masaryk University , Brno, Czech Republic

    Ivan Kopeček

  4. Masaryk University , Brno, Czech Republic

    Karel Pala

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Kanis, J. (2016). Digging Language Model – Maximum Entropy Phrase Extraction. In: Sojka, P., Horák, A., Kopeček, I., Pala, K. (eds) Text, Speech, and Dialogue. TSD 2016. Lecture Notes in Computer Science(), vol 9924. Springer, Cham. https://doi.org/10.1007/978-3-319-45510-5_6

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  • DOI: https://doi.org/10.1007/978-3-319-45510-5_6

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-45509-9

  • Online ISBN: 978-3-319-45510-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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