Lecture and presentation tracking in an intelligent meeting room

Abstract

Archiving, indexing, and later browsing through stored presentations and lectures is increasingly being used. We have investigated the special problems and advantages of lectures and propose the design and adaptation of a speech recognizer to a lecture such that the recognition accuracy can be significantly improved by prior analysis of the presented documents using a special class-based language model. We define a tracking accuracy measure which measures how well a system can automatically align recognized words with parts of a presentation and show that by prior exploitation of the presented documents, the tracking accuracy can be improved. The system described in this paper is part of an intelligent meeting room developed in the European Union-sponsored project FAME (Facilitating Agent for Multicultural Exchange).