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Pathological speech recognition based on images generated by the Kohonen neural network

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The nature of speech signal is very complicated, that causes that its visualisation 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 network for visualising speech signals uttered by children with a cleft palate was proposed. Speech signal is converted to its spectrum matrices representation, which constitutes the input for Kohonen neural network. 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.
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  • Automatic Control Department University of Mining and Metallurgy, al. Mickiewicza 30, 30-059 Kraków, mgajer@ia.agh.edu.pl
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bwmeta1.element.baztech-article-BAT2-0001-1293
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