Paper: Dialogue Act Tagging For Instant Messaging Chat Sessions

ACL ID P05-2014
Title Dialogue Act Tagging For Instant Messaging Chat Sessions
Venue Annual Meeting of the Association of Computational Linguistics
Session Main Conference
Year 2005
Authors

Instant Messaging chat sessions are real- time text-based conversations which can be analyzed using dialogue-act models. We describe a statistical approach for modelling and detecting dialogue acts in Instant Messaging dialogue. This in- volved the collection of a small set of task-based dialogues and annotating them with a revised tag set. We then dealt with segmentation and synchronisation issues which do not arise in spoken dialogue. The model we developed combines naive Bayes and dialogue-act n-grams to obtain better than 80% accuracy in our tagging experiment.