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Computer and Information Sciences – ISCIS 2006

Volume 4263 of the series Lecture Notes in Computer Science pp 230-238

Lexical Ambiguity Resolution for Turkish in Direct Transfer Machine Translation Models

  • A. Cüneyd TantuğAffiliated withCarnegie Mellon UniversityComputer Engineering Department, Istanbul Technical University Faculty of Eletrical-Electronic Engineering
  • , Eşref AdalıAffiliated withCarnegie Mellon UniversityComputer Engineering Department, Istanbul Technical University Faculty of Eletrical-Electronic Engineering
  • , Kemal OflazerAffiliated withCarnegie Mellon UniversityFaculty Of Engineering and Natural Sciences, Sabancı University

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Abstract

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.