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Statistical Machine Translation Using the Self-Organizing Map

  • V. F. López
  • J. M. Corchado
  • J. F. De Paz
  • S. Rodríguez
  • J. Bajo
Conference paper
  • 1.1k Downloads
Part of the Advances in Intelligent and Soft Computing book series (AINSC, volume 79)

Abstract

The paper describes a contextual environment using the Self-Organizing Map, which can model a semantic agent (SOMAgent) that learns the correct meaning of a word used in context in order to deal with specific phenomena such as ambiguity, and to generate more precise alignments that can improve the first choice of the Statistical Machine Translation system giving linguistic knowledge.

Keywords

Machine Translation Statistical Machine Translation Parallel Corpus Word Alignment Precise Alignment 
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 2010

Authors and Affiliations

  • V. F. López
    • 1
  • J. M. Corchado
    • 1
  • J. F. De Paz
    • 1
  • S. Rodríguez
    • 1
  • J. Bajo
    • 1
  1. 1.Dept. Informática y AutomáticaUniversity of SalamancaSalamancaSpain

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