@InProceedings{kanouchi-sudoh-komachi:2016:WAT2016,
  author    = {Kanouchi, Shin  and  Sudoh, Katsuhito  and  Komachi, Mamoru},
  title     = {Neural Reordering Model Considering Phrase Translation and Word Alignment for Phrase-based Translation},
  booktitle = {Proceedings of the 3rd Workshop on Asian Translation (WAT2016)},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {94--103},
  abstract  = {This paper presents an improved lexicalized reordering model for phrase-based
	statistical machine translation using a deep neural network.
	Lexicalized reordering suffers from reordering ambiguity, data sparseness and
	noises in a phrase table.
	Previous neural reordering model is successful to solve the first and second
	problems but fails to address the third one.
	Therefore,  we propose new features using phrase translation and word alignment
	to construct phrase vectors to handle inherently noisy phrase translation
	pairs.
	The experimental results show that our proposed method improves the accuracy of
	phrase reordering. 
	We confirm that the proposed method works well with phrase pairs including NULL
	alignments.},
  url       = {http://aclweb.org/anthology/W16-4607}
}