Learn More
This paper presents an overview of our ongoing work on dialogue-act classification. Results are presented on the ICSI, Switchboard, and on a selection of the AMI corpus, setting a baseline for forthcoming research. For these corpora the best accuracy scores obtained are 89.27%, 65.68% and 59.76%, respectively. We introduce a smart compression technique for(More)
This paper presents our efforts to create argument structures from meeting transcripts automatically. We show that unit labels of argument diagrams can be learnt and predicted by a computer with an accuracy of 78,52% and 51,43% on an unbalanced and balanced set respectively. We used a corpus of over 250 argument diagrams that was manually created by(More)
This paper continues the work described in Rienks and Heylen [2005] about argument diagramming of meeting discussions. In this paper we introduce the corpus that we created, discuss a user experiment about the usability of the technique, and show that the units of the diagram-ming method (segmented user utterances) can be learnt and predicted with an(More)
We address the problem of automatically detecting participant's influence levels in meetings. The impact and social psychological background are discussed. The more influential a participant is, the more he or she influences the outcome of a meeting. Experiments on 40 meetings show that application of statistical (both dynamic and static) models while using(More)
Virtual meeting rooms are used for simulation of real meeting behavior and can show how people behave, how they gesture, move their heads, bodies, their gaze behavior during conversations. They are used for visualising models of meeting behavior, and they can be used for the evaluation of these models. They are also used to show the effects of controlling(More)
In current meeting research we see modest attempts to visualize the information that has been obtained by either capturing and, probably more importantly, by interpreting the activities that take place during a meeting. The meetings being considered take place in smart meeting rooms. Cameras, microphones and other sensors capture meeting activities.(More)