We present an incremental annotation scheme and discourse model designed specifically for the study of consensus formation in collaborative meetings. By grounding the representation in observable contributions and enforcing a strict no-lookahead principle, the model provides a tractable way to analyse how decisions emerge over the course of interaction. The resulting structures are intentionally minimal yet expressive enough to capture the evolving task state and support dynamic visualisation and replay of the decision process. A web-based reference implementation of the model demonstrates how the evolving decision state can be inspected and replayed during analysis. Together with a suitable corpus, this framework provides a practical foundation for investigating the multimodal dynamics of collaborative decision-making in professional meetings.

We introduce the MEET corpus. The corpus was collected with the aim of systematically studying the effects of collocated (physical), remote (digital) and hybrid work meetings on collaborative decision-making. It consists of 10 sessions, where each session contains three recordings: a collocated, a remote and a hybrid meeting between three participants. The participants are working on a different survival ranking task during each meeting. The duration of each meeting ranges from 10 to 18 minutes, resulting in 380 minutes of conversation altogether. We also present the annotation scheme designed specifically to target our research questions. The recordings are currently being transcribed and annotated in accordance with this scheme