Eötvös Loránd University
We propose investigating human recollection of team meetings and how conversational AI could use this information to create better team cohesion in virtual settings
In this micro-project, we propose investigating human recollection of team meetings and how conversational AI could use this information to create better team cohesion in virtual settings.
Specifically, we would like to investigate how a person's emotion, personality, relationship to fellow teammates, goal and position in the meeting influences how they remember the meeting. We want to use this information to create memory aware conversational AI that could leverage such data to increase team cohesion in future meetings.
To achieve this goal, we plan first to record a multi-modal data-set of team meetings in a virtual-setting. Second, administrate questionnaires to participants in different time intervals succeeding a session. Third, annotate the corpus. Fourth, carry out an initial corpus analysis to inform the design of memory-aware conversational AI.
This micro-project will contribute to a longer-term effort in building a computational memory model for human-agent interaction.
This Humane-AI-Net micro-project was carried out by TU Delft (Catharine Oertel, Catholijn Jonker) and Eötvös Loránd University (ELTE, Andras Lorincz)