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The nature of speech signal is very complicated, that causes that its visualization and further analysis, without some initial pre-processing, is very complicated and doesn't always bring the desired effects. Speech signal in most cases is represented by videograms. The analysis of these forms of signal visualisation is not easy because of difficulties in their interpretation. In this article the usage of Kohonen neural networks for visualising speech signals uttered by children with a cleft palate was proposed. Speech signal is converted to its spectrum matrices representation, which in turn constitutes the input for Kohonen neural networks. Further a method for generating a simplified form of speech signal ( a poly=line figure) based on the network's output was presented. In addition a method for pathological speech signal recognition was presented. Test results based on utterances obtained from children with a cleft palate were presented.
Rocznik
Tom
Strony
117--122
Opis fizyczny
3 rys., 1 tabela, bibliogr. 9 poz.
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autor
autor
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- Automatic Control Department of the University of Mining and Metallurgy in Cracow, Al. Mickiewicza 30, 30-059 Cracow, Poland (Katedra Automatyki, Akademia Górniczo-Hutnicza), mkapusta@uci.agh.edu.pl
Bibliografia
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BPG1-0011-0076