Two-level classification for dialogue act recognition in task-oriented dialogues

Philippe Blache, Massina Abderrahmane, Stéphane Rauzy, Magalie Ochs, Houda Oufaida


Abstract
Dialogue act classification becomes a complex task when dealing with fine-grain labels. Many applications require such level of labelling, typically automatic dialogue systems. We present in this paper a 2-level classification technique, distinguishing between generic and specific dialogue acts (DA). This approach makes it possible to benefit from the very good accuracy of generic DA classification at the first level and proposes an efficient approach for specific DA, based on high-level linguistic features. Our results show the interest of involving such features into the classifiers, outperforming all other feature sets, in particular those classically used in DA classification.
Anthology ID:
2020.coling-main.431
Volume:
Proceedings of the 28th International Conference on Computational Linguistics
Month:
December
Year:
2020
Address:
Barcelona, Spain (Online)
Venue:
COLING
SIG:
Publisher:
International Committee on Computational Linguistics
Note:
Pages:
4915–4925
Language:
URL:
https://www.aclweb.org/anthology/2020.coling-main.431
DOI:
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PDF:
http://aclanthology.lst.uni-saarland.de/2020.coling-main.431.pdf