| AMIengagement tool increases the sense of presence for users who join a meeting by cellphone: the cartoon images dynamically indicate who is looking at whom during the meeting.
Images courtesy of the AMI Consortium | Can you quickly catch up on a meeting for which you are late? Can you easily track back through meeting archives to discover why a particular decision was taken?
These are some of the key questions addressed by the AMI Consortium, a project using grid computing to better understand human communication in meetings.
Technology to enhance collaboration
When people meet, their communication is spread across a number of modalities: the spoken word, gestures, postures, intonation and timing. AMI aims to capture these signals using an instrumented meeting room, equipped with multiple video cameras and microphones, along with devices to capture handwriting, whiteboard activity and projected data. The AMI project makes sense of the captured signals using speech recognition, video and multimodal processing, and language processing techniques such as automatic summarization and the segmentation of a discussion into topics. These are computationally challenging recognition tasks: for example, the recognition of speech recorded using tabletop microphones requires considerable extensions to the state-of-the-art, especially given the casual, conversational and overlapping style of speech in meetings. Meeting-support applications
AMI is using these captured, recognized signals in applications that improve engagement and efficiency. Applications include:
• Meeting browsers, which automatically generate meeting summaries and enable meetings to be indexed so users can search and browse archives for relevant material.
• Content linking, which uses recognized words to automatically retrieve related documents and relevant meeting segments during an ongoing meeting.
• Phone conference interfaces, which provide remote users with an indication of who is looking at whom during meetings. | 
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