@InProceedings{jalilisabet-faili-haffari:2016:COLING,
  author    = {Jalili Sabet, Masoud  and  Faili, Heshaam  and  Haffari, Gholamreza},
  title     = {Improving Word Alignment of Rare Words with Word Embeddings},
  booktitle = {Proceedings of COLING 2016, the 26th International Conference on Computational Linguistics: Technical Papers},
  month     = {December},
  year      = {2016},
  address   = {Osaka, Japan},
  publisher = {The COLING 2016 Organizing Committee},
  pages     = {3209--3215},
  abstract  = {We address the problem of inducing word alignment for language pairs by
	developing an unsupervised model with the capability of getting applied to
	other generative alignment models.  We approach the task by: i)proposing a new
	alignment model based on the IBM alignment model 1 that uses vector
	representation of words, and ii)examining the use of similar source words
	to overcome the problem of rare source words and improving the alignments. We
	apply our method to English-French corpora and run the experiments with
	different sizes of sentence pairs. Our results show competitive performance
	against the baseline and in some cases improve the results up to 6.9% in terms
	of precision.},
  url       = {http://aclweb.org/anthology/C16-1302}
}