A rule-driven dynamic programming decoder for statistical MT

  • Authors:
  • Christoph Tillmann

  • Affiliations:
  • IBM T.J. Watson Research Center, Yorktown Heights, N.Y.

  • Venue:
  • SSST '08 Proceedings of the Second Workshop on Syntax and Structure in Statistical Translation
  • Year:
  • 2008

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Abstract

The paper presents an extension of a dynamic programming (DP) decoder for phrase-based SMT (Koehn, 2004; Och and Ney, 2004) that tightly integrates POS-based re-order rules (Crego and Marino, 2006) into a left-to-right beam-search algorithm, rather than handling them in a pre-processing or re-order graph generation step. The novel decoding algorithm can handle tens of thousands of rules efficiently. An improvement over a standard phrase-based decoder is shown on an Arabic- English translation task with respect to translation accuracy and speed for large re-order window sizes.