@InProceedings{ostling:2016:COLING,
  author    = {\"{O}stling, Robert},
  title     = {A Bayesian model for joint word alignment and part-of-speech transfer},
  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     = {620--629},
  abstract  = {Current methods for word alignment require considerable amounts of
	parallel text to deliver accurate results, a requirement which is met only for
	a small minority of the world's approximately 7,000 languages.
	We show that by jointly performing word alignment and annotation transfer in
	a novel Bayesian model, alignment accuracy can be
	improved for language pairs where annotations are available for only
	one of the languages---a finding which could facilitate the study and
	processing of a vast number of low-resource languages.
	We also present an evaluation where our method is used to perform
	single-source and multi-source part-of-speech transfer with 22 translations
	of the same text in four different languages. This allows us to quantify the
	considerable variation in accuracy depending on the specific source text(s)
	used, even with different translations into the same language.},
  url       = {http://aclweb.org/anthology/C16-1060}
}