Funding: NSF (1998) Experimental Software Systems "Automated Understanding of Captured Experience"

Award#9806822 – Experimental Software Systems: Automated Understanding of Captured Experience
ABSTRACT
9806822 Essa, Irfan A. Abowd, Gregory D. Georgia Institute of Technology Experimental Software Systems: Automated Understanding of Captured Experience The objective of this research is to reduce substantially the human input necessary for creating and accessing large collections of multimedia, particularly multimedia created by capturing what is happening in an environment. The existing software system which is being used as the starting point for this investigation is Classroom 2000, a system designed to capture what happens in classrooms, meetings, and offices. Classroom 2000 integrates and synchronizes multiple streams of captured text, images, handwritten annotations, audio, and video. In a sense, it automates note-taking for a lecture or meeting. The research challenge is to make sense of this flood of captured data. The project explores how the output of Classroom 2000 can be automatically structured, segmented, indexed, and linked. Machine learning and statistical approaches to language are used to attempt to understand the captured data. Techniques from computational perception are used to try to find structure in the captured data. An important component of this research is the experimental analysis of the software system being built. The expectation is that this research will have a dramatic impact on how humans work and learn, as technology aids humans by capturing and making accessible what happens in an environment.