@inproceedings{caines-etal-2017-collecting,
    title = "Collecting fluency corrections for spoken learner {E}nglish",
    author = "Caines, Andrew  and
      Flint, Emma  and
      Buttery, Paula",
    editor = "Tetreault, Joel  and
      Burstein, Jill  and
      Leacock, Claudia  and
      Yannakoudakis, Helen",
    booktitle = "Proceedings of the 12th Workshop on Innovative Use of {NLP} for Building Educational Applications",
    month = sep,
    year = "2017",
    address = "Copenhagen, Denmark",
    publisher = "Association for Computational Linguistics",
    url = "https://preview.aclanthology.org/iwcs-25-ingestion/W17-5010/",
    doi = "10.18653/v1/W17-5010",
    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."
}