Lecture and Presentation Tracking in an Intelligent Meeting Room

Abstract

Archiving, indexing, and later browsing through stored presentations and lectures is a task that can be observed with a growing frequency. We have investigated thespecial problems and advantages of lectures and propose the design and adaptation of a speech recognizer towards a lecture such that the recognition accuracy can be signi cantly 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).