Are you being addressed?: real-time addressee detection to support remote participants in hybrid meetings

摘要

A meeting assistant agent for (remote) participants in hybrid meetings has been developed. Its task is to monitor the meeting conversation and notify the user when he is being addressed. This paper presents the experimentsudthat have been performed to develop machine classifiers to decide if “Youudare being addressed” where “You” refers to a fixed (remote) participant in a meeting. The experimental results back up the choices made regarding the selection of data, features, and classification methods. We discuss variations of the addressee classification problem that have been considered in the literature and how suitable they are for addressing detection in a system that plays a role in a live meeting.