Speech is gradually becoming more important as a source of information in knowledge management and text search systems. We present a system that analyzes a speech data stream and automatically finds documents related to the current topic of discussion in the speech stream. Experimental results show that the system generates result lists with an average precision at 10 hits of better than 60%. We also present a hit-list reranking technique based on named entity analysis and automatic text categorization that can improve the search results by 6%-12%.
By: Anni R. Coden, Eric W. Brown
Published in: RC22341 in 2002
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