Summary of the paper

Title A Three-stage Disfluency Classifier for Multi Party Dialogues
Authors Margot Mieskes and Michael Strube
Abstract We present work on a three-stage system to detect and classify disfluencies in multi party dialogues. The system consists of a regular expression based module and two machine learning based modules. The results are compared to other work on multi party dialogues and we show that our system outperforms previously reported ones.
Language Single language
Topics Dialogue & Natural Interactivity, Corpus (creation, annotation, etc.), Discourse
Full paper A Three-stage Disfluency Classifier for Multi Party Dialogues
Slides A Three-stage Disfluency Classifier for Multi Party Dialogues
Bibtex @InProceedings{MIESKES08.665,
  author = {Margot Mieskes and Michael Strube},
  title = {A Three-stage Disfluency Classifier for Multi Party Dialogues},
  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 = {http://www.lrec-conf.org/proceedings/lrec2008/},
  language = {english}
  }

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