@InProceedings{caines-flint-buttery:2017:BEA,
  author    = {Caines, Andrew  and  Flint, Emma  and  Buttery, Paula},
  title     = {Collecting fluency corrections for spoken learner English},
  booktitle = {Proceedings of the 12th Workshop on Innovative Use of NLP for Building Educational Applications},
  month     = {September},
  year      = {2017},
  address   = {Copenhagen, Denmark},
  publisher = {Association for Computational Linguistics},
  pages     = {91--100},
  abstract  = {We present crowdsourced collection of error annotations for transcriptions of
	spoken learner English. Our emphasis in data collection is on fluency
	corrections, a more complete correction than has traditionally been aimed for
	in grammatical error correction research (GEC). Fluency corrections require
	improvements to the text, taking discourse and utterance level semantics into
	account: the result is a more naturalistic, holistic version of the original.
	We propose that this shifted emphasis be reflected in a new name for the task:
	'holistic error correction' (HEC). We analyse crowdworker behaviour in HEC and
	conclude that the method is useful with certain amendments for future work.},
  url       = {http://www.aclweb.org/anthology/W17-5010}
}