A Syntax-based Statistical Translation Model

We present a syntax-based statistical translation model. Our model transforms a source-language parse tree into a target-language string by applying stochastic operations at each node. These operations capture linguistic differences such as word order and case marking. Model parameters are estimated in polynomial time using an EM algorithm. The model produces word alignments that are better than those produced by IBM Model 5.

• Publication year

  2001

• Venue

  Annual Meeting of the Association for Computational Linguistics

• Publication date

  2001-07-06

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1073012.1073079
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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