We describe a system that tracks conversational context using speech
recognition and topic modeling. Topics are described by computing the
frequency of words for each class. We thus reliably detect, in
real-time, the currently active topic of a group discussion involving
several individuals. One application of this 'situational awareness'
is a computer that acts as a mediator of the group meeting,
offering feedback and relevant questions to stimulate further
conversation. It also provides a temporal analysis of the meeting's
evolution. We demonstrate this application and discuss other possible
impacts of conversational situation awareness.
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