Open Access

Robust Techniques for Organizing and Retrieving Spoken Documents

EURASIP Journal on Advances in Signal Processing20032003:980946

DOI: 10.1155/S1110865703211070

Received: 5 April 2002

Published: 25 February 2003

Abstract

Information retrieval tasks such as document retrieval and topic detection and tracking (TDT) show little degradation when applied to speech recognizer output. We claim that the robustness of the process is because of inherent redundancy in the problem: not only are words repeated, but semantically related words also provide support. We show how document and query expansion can enhance that redundancy and make document retrieval robust to speech recognition errors. We show that the same effect is true for TDT′s tracking task, but that recognizer errors are more of an issue for new event and story link detection.

Keywords

spoken document retrieval topic detection and tracking information retrieval

Authors’ Affiliations

(1)
Center for Information Retrieval, Department of Computer Science, University of Massachusetts

Copyright

© Copyright © 2003 Hindawi Publishing Corporation 2003