We describe a process for automatically detecting decision-making sub-dialogues in multi-party, human-human meetings in real-time. Our basic approach to decision detection involves distinguishing between different utterance types based on the roles that they play in the formulation of a decision. In this paper, we describe how this approach can be implemented in real-time, and show that the resulting system’s performance compares well with other detectors, including an off-line version.