Lexical Access-based Confidence Measure for a Spanish Keyword Spotting System
نویسندگان
چکیده
Keyword spotting deals with the search of a reduced set of keywords in audio content. Phone Lattice-based approaches are very fast but achieve poor results. HMM-based keyword spotting systems deal with filler models to absorb the Out-of-vocabulary (OOV) words and achieve best results although they are slower. We propose a technique which combines them in order to perform a confidence measure to reduce the false alarm rate achieved in the HMM-based keyword spotting module over a Spanish Keyword Spotting system. Different filler models are investigated within the experiments.
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