Addressee Identification in Face-to-Face Meetings 
 We present results on addressee identification in four-participants face-to-face meetings using Bayesian Network and Naive Bayes classifiers . First, we investigate how well the addressee of a dialogue act can be predicted based on gaze , utterance and conversational context features . Then, we explore whether information about meeting context can aid classifiers ' performances . Both classifiers perform the best when conversational context and utterance features are combined with speaker's gaze information . The classifiers show little gain from information about meeting context . 