Meeting Adjourned: Off-line Learning Interfaces for Automatic Meeting Understanding

Abstract

Upcoming technologies will automatically identify and extract certain types of general information from meetings, such as topics and the tasks people agree to do. We explore interfaces for presenting this information to users after a meeting is completed, using two post-meeting interfaces that display information from topics and action items respectively. These interfaces also provide an excellent forum for obtaining user feedback about the performance of classification algorithms, allowing the system to learn and improve with time. We describe how we manage the delicate balance of obtaining necessary feedback without overburdening users. We also evaluate the effectiveness of feedback from one interface on improvement of future action item detection.

Keywords: Artificial Intelligence, Artificial Intelligence Center, AIC