Score Normalization for Keyword Search
Bogazici University Istanbul Turkey
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In this work, keyword search KWS is based on a symbolic index that uses posteriorgram representation of the speech data. For each query, sum-to-one normalization or keyword specific thresholding is applied to the search results. The effect of these methods on the proposed KWS system is investigated. Results are combined with a KWS system that is based on an index generated from automatic speech recognition ASR lattices and the effect of score normalization on the performance of the combined system is observed. Maximum term weighted value MTWV is used as the performance measure. It is shown that the MTWV is increased in the combined system especially for the out-of-vocabulary OOV keywords that are not covered by the ASR lexicon.
- Voice Communications