@InProceedings{han-schlangen:2017:EACLshort,
  author    = {Han, Ting  and  Schlangen, David},
  title     = {Grounding Language by Continuous Observation of Instruction Following},
  booktitle = {Proceedings of the 15th Conference of the European Chapter of the Association for Computational Linguistics: Volume 2, Short Papers},
  month     = {April},
  year      = {2017},
  address   = {Valencia, Spain},
  publisher = {Association for Computational Linguistics},
  pages     = {491--496},
  abstract  = {Grounded semantics is typically learnt from utterance-level meaning
	representations (e.g., successful database retrievals, denoted objects in
	images, moves in a game). We explore learning word and utterance meanings by
	continuous observation of the actions of an instruction follower (IF). While an
	instruction giver (IG) provided a verbal description of a configuration of
	objects, IF recreated it using a GUI. Aligning these GUI actions to sub-
	utterance chunks allows a simple maxi- mum entropy model to associate them as
	chunk meaning better than just providing it with the utterance-final
	configuration. This shows that semantics useful for incremental (word-by-word)
	application, as required in natural dialogue, might also be better acquired
	from incremental settings.},
  url       = {http://www.aclweb.org/anthology/E17-2079}
}