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Grammatical Inference for Syntax-Based Statistical Machine Translation

  • Menno van Zaanen
  • Jeroen Geertzen
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 4201)

Abstract

In this article we present a syntax-based translation system, called TABL (Translation using Alignment-Based Learning). It translates natural language sentences by mapping grammar rules (which are induced by the Alignment-Based Learning grammatical inference framework) of the source language to those of the target language. By parsing a sentence in the source language, the grammar rules in the derivation are translated using the mapping and subsequently, a derivation in the target language is generated. The initial results are encouraging, illustrating that this is a valid machine translation approach.

Keywords

Machine Translation Target Language Plain Text Source Language Derivation Tree 
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.

References

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    Brown, P.F., Della Pietra, S.A., Della Pietra, V.J., Mercer, R.L.: The mathematics of statistical machine translation: Parameter estimation. Computational Linguistics 19, 263–312 (1993)Google Scholar
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    Dan Melamed, I.: Statistical machine translation by parsing. In: 42th Annual Meeting of the Association for Computational Linguistics, Barcelona, Spain (2004)Google Scholar
  3. 3.
    Probst, K.: Automatically Induced Syntactic Transfer Rules for Machine Translation under a Very Limited Data Scenario. PhD thesis, Carnegie Mellon University, Pittsburgh, PA, USA (2005)Google Scholar
  4. 4.
    van Zaanen, M.: Bootstrapping Structure into Language: Alignment-Based Learning. PhD thesis, University of Leeds, Leeds, UK (January 2002)Google Scholar

Copyright information

© Springer-Verlag Berlin Heidelberg 2006

Authors and Affiliations

  • Menno van Zaanen
    • 1
  • Jeroen Geertzen
    • 2
  1. 1.Division of Information and Communication Sciences, Department of ComputingMacquarie UniversitySydneyAustralia
  2. 2.Language and Information ScienceTilburg UniversityTilburgThe Netherlands

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