Toward a scoring function for quality-driven machine translation

  • Authors:
  • Douglas A. Jones;Gregory M. Rusk

  • Affiliations:
  • Department of Defense, Fort Meade, MD;RABA Technologies, Columbia, MD

  • Venue:
  • COLING '00 Proceedings of the 18th conference on Computational linguistics - Volume 1
  • Year:
  • 2000

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Abstract

We describe how we constructed an automatic scoring function for machine translation quality; this function makes use of arbitrarily many pieces of natural language processing software that has been designed to process English language text. By machine-learning values of functions available inside the software and by constructing functions that yield values based upon the software output, we are able to achieve preliminary, positive results in machine-learning the difference between human-produced English and machine-translation English. We suggest how the scoring function may be used for MT system development.