Paper: Addressee Identification In Face-To-Face Meetings

ACL ID E06-1022
Title Addressee Identification In Face-To-Face Meetings
Venue Annual Meeting of The European Chapter of The Association of Computational Linguistics
Session Main Conference
Year 2006
Authors

We present results on addressee identifica- tion in four-participants face-to-face meet- ings using Bayesian Network and Naive Bayes classifiers. First, we investigate how well the addressee of a dialogue act can be predicted based on gaze, ut- terance and conversational context fea- tures. Then, we explore whether informa- tion about meeting context can aid classi- fiers’ performances. Both classifiers per- form the best when conversational context and utterance features are combined with speaker’s gazeinformation. Theclassifiers show little gain from information about meeting context.