EFFICIENT METHODS FOR DETECTING KEYWORDS IN CONTINUOUS SPEECH

This paper refers to our prosperous development of algorithms for detecting keywords in continuous speech. Two different approaches to define confidence measures are introduced. As an advantage, these definitions are theoretically calculable without artful tuning. Moreover, two distinct decoding algorithms are presented, that incorporate these confidence measures into the search procedure. One is a new possibility of detecting keywords in continuous speech, using the standard Viterbi algorithm without modeling the non-keyword parts of the utterance. The other one is an improved further development of an algorithm described in [1], also without the need of modeling the non-keyword parts.

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