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} } |