Summary of the paper

Title Cross-Domain Dialogue Act Tagging
Authors Nick Webb, Ting Liu, Mark Hepple and Yorick Wilks
Abstract We present recent work in the area of Cross-Domain Dialogue Act (DA) tagging. We have previously reported on the use of a simple dialogue act classifier based on purely intra-utterance features - principally involving word n-gram cue phrases automatically generated from a training corpus. Such a classifier performs surprisingly well, rivalling scores obtained using far more sophisticated language modelling techniques. In this paper, we apply these automatically extracted cues to a new annotated corpus, to determine the portability and generality of the cues we learn.
Language Language-independent
Topics Dialogue & Natural Interactivity, Corpus (creation, annotation, etc.), Acquisition, Machine Learning
Full paper Cross-Domain Dialogue Act Tagging
Slides -
Bibtex @InProceedings{WEBB08.502,
  author = {Nick Webb, Ting Liu, Mark Hepple and Yorick Wilks},
  title = {Cross-Domain Dialogue Act Tagging},
  booktitle = {Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)},
  year = {2008},
  month = {may},
  date = {28-30},
  address = {Marrakech, Morocco},
  editor = {Nicoletta Calzolari (Conference Chair), Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias},
  publisher = {European Language Resources Association (ELRA)},
  isbn = {2-9517408-4-0},
  note = {},
  language = {english}

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