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Neural machine Translation

Statistical Machine Translation

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Lexical Choice

Related to the problem of translating words is the problem of word sense disambiguation. When a word has several senses, these senses may have different translation. Lexical choice in translation may be aided by more contextual or other clues.

Lexical Choice is the main subject of 42 publications. 5 are discussed here.

Publications

Already early work (Brown et al., 1991) tried to integrate word sense disambiguation methods in statistical machine translation. These methods include local (García-Varea et al., 2001) or broader context (Vickrey et al., 2005), or dictionary information (Lee and Kim, 2002) in the lexical translation decision, although straight-forward application of word sense disambiguation methods does not always lead to improvements (Carpuat and Wu, 2005).

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New Publications

  • Tyers et al. (2015)
  • Marie and Apidianaki (2015)
  • Herrmann et al. (2015)
  • Tang et al. (2016)
  • Su et al. (2015)
  • Camacho-Collados et al. (2015)
  • Aminian et al. (2015)
  • Rudnick and Gasser (2013)
  • Casteleiro et al. (2014)
  • Killman (2014)
  • Xiong and Zhang (2014)
  • Ha et al. (2014)
  • Niehues and Waibel (2013)
  • Carpuat (2013)
  • Ananthakrishnan et al. (2013)
  • Huck et al. (2011)
  • Huck et al. (2010)
  • Lai et al. (2012)
  • Tyers et al. (2012)
  • Vintar et al. (2012)
  • Bansal et al. (2012)
  • Yao et al. (2012)
  • Apidianaki et al. (2012)
  • Arcan et al. (2012)
  • Chiang et al. (2011)
  • Hasan et al. (2008)
  • Hasan and Ney (2009)
  • Patry and Langlais (2009)
  • Yang and Kirchhoff (2010)
  • Chen et al. (2010)
  • Apidianaki (2009)
  • Carpuat (2009)
  • Tsunakawa and Kaji (2010)
  • Lefever and Hoste (2011)
  • Chung and Lee (2005)
  • Mostow and Duan (2011)
  • Li and Li (2002)

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