|Department of Engineering|
|University of Cambridge > Engineering Department > Machine Intelligence Lab|
GENERAL QUERY EXPANSION TECHNIQUES FOR SPOKEN DOCUMENT RETRIEVAL
P. Jourlin, S.E. Johnson , K. Sparck Jones & P.C. Woodland
This paper presents some developments in query expansion and document representation of our Spoken Document Retrieval (SDR) system since the 1998 Text REtrieval Conference (TREC-7).
We have shown that a modification of the document representation combining several techniques for query expansion can improve Average Precision by 17% relative to a system similar to that which we presented at TREC-7. These new experiments have also confirmed that the degradation of Average Precision due to a Word Error Rate (WER) of 25% is relatively small (around 2% relative). We hope to repeat these experiments when larger document collections become available to evaluate the scalability of these techniques.
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