Lexical Ambiguity Resolution for Turkish in Direct Transfer Machine Translation Models

  • A. Cüneyd Tantuğ
  • Eşref Adalı
  • Kemal Oflazer
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4263)


This paper presents a statistical lexical ambiguity resolution method in direct transfer machine translation models in which the target language is Turkish. Since direct transfer MT models do not have full syntactic information, most of the lexical ambiguity resolution methods are not very helpful. Our disambiguation model is based on statistical language models. We have investigated the performances of some statistical language model types and parameters in lexical ambiguity resolution for our direct transfer MT system.


Machine Translation Target Language Direct Transfer Training Corpus Word Sense Disambiguation 
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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Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • A. Cüneyd Tantuğ
    • 1
  • Eşref Adalı
    • 1
  • Kemal Oflazer
    • 2
  1. 1.Computer Engineering DepartmentIstanbul Technical University Faculty of Eletrical-Electronic EngineeringIstanbulTürkiye
  2. 2.Faculty Of Engineering and Natural SciencesSabancı UniversityTuzlaTürkiye

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