Exact decoding of syntactic translation models through Lagrangian relaxation

  • Authors:
  • Alexander M. Rush;Michael Collins

  • Affiliations:
  • MIT CSAIL, Cambridge, MA;Columbia University, New York, NY

  • Venue:
  • HLT '11 Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies - Volume 1
  • Year:
  • 2011

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Abstract

We describe an exact decoding algorithm for syntax-based statistical translation. The approach uses Lagrangian relaxation to decompose the decoding problem into tractable sub-problems, thereby avoiding exhaustive dynamic programming. The method recovers exact solutions, with certificates of optimality, on over 97% of test examples; it has comparable speed to state-of-the-art decoders.