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Machine Translation

, Volume 19, Issue 1, pp 83–112 | Cite as

The Long-Term Forecast for Weather Bulletin Translation

  • Philippe Langlais
  • Simona Gandrabur
  • Thomas Leplus
  • Guy Lapalme
Article

Abstract

Machine Translation (MT) is the focus of extensive scientific investigations driven by regular evaluation campaigns, but which are mostly oriented towards a somewhat particular task: translating news articles into English. In this paper, we investigate how well current MT approaches deal with a real-world task. We have rationally reconstructed one of the only MT systems in daily use which produces high-quality translation: the Météo system. We show how a combination of a sentence-based memory approach, a phrase-based statistical engine and a neural-network rescorer can give results comparable to those of the current system. We also explore another possible prospect for MT technology: the translation of weather alerts, which are currently being translated manually by translators at the Canadian Translation Bureau.

Keywords

corpus-based MT Translation Memory statistical MT bootstrapping rescoring Météo 

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Copyright information

© Springer 2006

Authors and Affiliations

  • Philippe Langlais
    • 1
  • Simona Gandrabur
    • 1
  • Thomas Leplus
    • 1
  • Guy Lapalme
    • 1
  1. 1.DIRO/RALI, Département d’informatique et de recherche opérationnelleUniversité de MontréalMontréalCanada

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