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ACL
2009

A Statistical Machine Translation Model Based on a Synthetic Synchronous Grammar

13 years 1 months ago
A Statistical Machine Translation Model Based on a Synthetic Synchronous Grammar
Recently, various synchronous grammars are proposed for syntax-based machine translation, e.g. synchronous context-free grammar and synchronous tree (sequence) substitution grammar, either purely formal or linguistically motivated. Aiming at combining the strengths of different grammars, we describes a synthetic synchronous grammar (SSG), which tentatively in this paper, integrates a synchronous context-free grammar (SCFG) and a synchronous tree sequence substitution grammar (STSSG) for statistical machine translation. The experimental results on NIST MT05 Chinese-to-English test set show that the SSG based translation system achieves significant improvement over three baseline systems.
Hongfei Jiang, Muyun Yang, Tiejun Zhao, Sheng Li,
Added 16 Feb 2011
Updated 16 Feb 2011
Type Journal
Year 2009
Where ACL
Authors Hongfei Jiang, Muyun Yang, Tiejun Zhao, Sheng Li, Bo Wang
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