Abstract: In this paper we present our recent work in implementing a keyword spotting system for detecting a limited number of keywords in continuous speech of Serbian. The keywords are detecting without modeling the non-keyword parts of the sentence using confidence measure and HMMs (Hidden Markov Models). Only keywords have to be model by HMMs in the way which we propose in this paper, that each syllable is three-state HMM. In this paper we also introduce MSQ - measure of system's quality in order to determine optimal step and optimal threshold for the confidence measure in the decoding phase. The obtained results show that proposed procedure can be used in interactive man-machine dialogue services.
Key words: Hidden Markov models, speech recongnition, man-machine dialogue.