Abstract-The paper presents unsupervised method for word detection in recorded spoken language signal. The method is based on examining signal similarity of two analyzed media description: registered voice and a word (textual query) synthesized by using Text-to-Speech tools. The descriptions of media were given by a sequence of Mel-Frequency Cepstral Coefficients or Human-Factor Cepstral Coefficients. Dynamic Time Warping algorithm has been applied to provide time alignment of the given media description. The detection involved classification method based on cost function, calculated upon signal similarity and alignment path. Potential false matches were eliminated in the algorithm by comparing costs of the path subsequences to a threshold value. The results of the work could provide incentives to build affordable commercial or non-commercial solutions for specific and multilingual applications.Index Terms-Speech processing, speech analysis, pattern matching, keyword search, audio information retrieval

Index Terms-keyword spotting, formant frequency analysis, pattern matching, audio information retrieval

The paper describes an evaluation of the application of selected similarity functions in the task of keyword spotting. Experiments were carried out in the Polish language. The research results can be used to improve already existing keyword spotting methods, or to develop new ones.

The paper presents the application of unsupervised method to word detection in recorded speech for the spoken Polish language. The method utilizes similarity measure between analyzed speech and a pattern synthesized from pure text. Dynamic time warping algorithm is applied for time alignment and the resulting alignment path defines an input to the classifier. The classification process involves calculation of cost function and extraction of the projected sequence of Human-Factor Cepstral Coefficients, both of which are compared with the threshold values. The results obtained after application of the method to the CLARIN-PL Mobile Corpus are encouraging to develop this method for the Polish language.Communication