Cross-Domain Dialogue Act Tagging

Nick Webb, Ting Liu, Mark Hepple, 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.
Anthology ID:
L08-1492
Volume:
Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08)
Month:
May
Year:
2008
Address:
Marrakech, Morocco
Editors:
Nicoletta Calzolari, Khalid Choukri, Bente Maegaard, Joseph Mariani, Jan Odijk, Stelios Piperidis, Daniel Tapias
Venue:
LREC
SIG:
Publisher:
European Language Resources Association (ELRA)
Note:
Pages:
Language:
URL:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/502_paper.pdf
DOI:
Bibkey:
Cite (ACL):
Nick Webb, Ting Liu, Mark Hepple, and Yorick Wilks. 2008. Cross-Domain Dialogue Act Tagging. In Proceedings of the Sixth International Conference on Language Resources and Evaluation (LREC'08), Marrakech, Morocco. European Language Resources Association (ELRA).
Cite (Informal):
Cross-Domain Dialogue Act Tagging (Webb et al., LREC 2008)
Copy Citation:
PDF:
http://www.lrec-conf.org/proceedings/lrec2008/pdf/502_paper.pdf