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both manual and automatic transcriptions, for non-English documents, we use automatic translations. In this work, we use AdaBoost, a discriminative classification method with both lexical and semantic features. The results indicate 11%-13% relative improvement over a baseline keyword-spotting-based approach. We also show
This paper addresses the problem of integrating speech and text content sources for the document search problem, as well as its usefulness from an ad-hoc retrieval -keyword search - point of view. Position specific posterior latices (PSPL) is naturally extended to deal with both speech and text content, where a new
approach compares the underlying acoustic models of keywords and a target database to alleviate the impact of mismatched vocabulary and language model, e.g. different domains. Experimental results on the Wall Street Journal (WSJ) database show that the proposed approach achieves a comparable performance, compared with the
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