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Incremental Learning of Transfer Rules for Customized Machine Translation

  • Conference paper
Applications of Declarative Programming and Knowledge Management (INAP 2004, WLP 2004)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 3392))

Abstract

In this paper we present a machine translation system, which translates Japanese into German. We have developed a transfer-based architecture in which the transfer rules are learnt incrementally from translation examples provided by a user. This means that there are no handcrafted rules, but, on the contrary, the user can customize the system according to his own preferences. The translation system has been implemented by using Amzi! Prolog. This programming environment had the big advantage of offering sufficient scalability even for large lexicons and rule bases, powerful unification operations for the application of transfer rules, and full Unicode support for Japanese characters. Finally, the application programming interface to Visual Basic made it possible to design an embedded translation environment so that the user can use Microsoft Word to work with the Japanese text and invoke the translation features directly from within the text editor. We have integrated the machine translation system into a language learning environment for German-speaking language students to create a Personal Embedded Translation and Reading Assistant (PETRA).

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Author information

Authors and Affiliations

  1. Faculty of Computer Science, University of Vienna, Liebiggasse 4, A-1010, Vienna, Austria

    Werner Winiwarter

Authors
  1. Werner Winiwarter
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Editor information

Editors and Affiliations

  1. Universität Würzburg, Am Hubland, 97074, Würzburg, Germany

    Dietmar Seipel

  2. Institut für Informatik, CAU Kiel, Germany

    Michael Hanus

  3. Fraunhofer FIRST, Berlin

    Ulrich Geske

  4. IF Computer Japan, 5-28-2 Sendagi, Bunkyo-ku, 113-0022, Tokyo, Japan

    Oskar Bartenstein

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© 2005 Springer-Verlag Berlin Heidelberg

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Winiwarter, W. (2005). Incremental Learning of Transfer Rules for Customized Machine Translation. In: Seipel, D., Hanus, M., Geske, U., Bartenstein, O. (eds) Applications of Declarative Programming and Knowledge Management. INAP WLP 2004 2004. Lecture Notes in Computer Science(), vol 3392. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11415763_4

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  • DOI: https://doi.org/10.1007/11415763_4

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-25560-4

  • Online ISBN: 978-3-540-32124-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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