Citation: Communication Papers of the 2018 Federated Conference on Computer Science and Information Systems, M. Ganzha, L. Maciaszek, M. Paprzycki (eds). ACSIS, Vol. 17, pages 123–127 (2018)
Abstract. 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.
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