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 |
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| 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 = {http://www.lrec-conf.org/proceedings/lrec2008/}, language = {english} } |