SPMT: Statistical Machine Translation with Syntactified Target Language Phrases

We introduce SPMT, a new class of statistical Translation Models that use Syntactified target language Phrases. The SPMT models outperform a state of the art phrase-based baseline model by 2.64 Bleu points on the NIST 2003 Chinese-English test corpus and 0.28 points on a human-based quality metric that ranks translations on a scale from 1 to 5.

• Publication year

  2006

• Venue

  Conference on Empirical Methods in Natural Language Processing

• Publication date

  2006-07-22

• Fields of study

  Linguistics, Computer Science

• Identifiers
  DOI 10.3115/1610075.1610083
• 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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