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Decoding for Syntax Based Models

Decoding for models based on synchronous grammars require fundamentally different decoding algorithms than phrase-based models. Most of these algorithms are extensions of monolingual syntactic parsing.

Syntax Model Decoding is the main subject of 52 publications. 6 are discussed here.

Publications

The use of n-gram language models in tree-generating decoding increases computational complexity significantly. One solution is to do a first pass translation without the language model, and then score the pruned search hyper graph in a second pass with the language model (Venugopal et al., 2007). Our presentation of cube pruning follows the description of Huang and Chiang (2007). Some more implementation details are presented by Li and Khudanpur (2008). To enable more efficient pruining, outside cost estimates may be obtained by first decoding with a lower-order n-gram model (Zhang and Gildea, 2008). Xiong et al. (2008) introduce reordering constraints based on punctuation and maximum reordering distance for tree-based decoding.

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New Publications

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  • Gildea (2011)
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  • Heafield et al. (2011)
  • Liu and Liu (2010)
  • Gildea (2012)
  • Peitz et al. (2012)
  • Braune et al. (2012)
  • Maletti (2012)
  • Lagoutte et al. (2012)
  • Feng et al. (2012)
  • Gesmundo et al. (2012)
  • Quernheim and Knight (2012)
  • Blunsom and Osborne (2008)
  • Petrov et al. (2008)
  • DeNero et al. (2009)
  • Li and Khudanpur (2009)
  • Carreras and Collins (2009)
  • Hopkins and Langmead (2009)
  • Pust and Knight (2009)
  • DeNero et al. (2009)
  • Hopkins and Langmead (2010)
  • Huang and Mi (2010)
  • Gesmundo and Henderson (2010)
  • Lopez (2009)
  • Saers and Wu (2011)
  • Bodenstab et al. (2011)
  • Chung et al. (2011)
  • Crescenzi et al. (2011)
  • Rush and Collins (2011)
  • Vaswani et al. (2011)
  • Zhu and Xiao (2011)
  • Gesmundo and Henderson (2011)
  • Watanabe and Sumita (2003)
  • Huang (2006)
  • Huang (2008)

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