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Neural Computing and Applications

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01.10.2009 | Original Article

Speech nonfluency detection using Kohonen networks

verfasst von: Izabela Szczurowska, Wiesława Kuniszyk-Jóźkowiak, Elżbieta Smołka

Erschienen in: Neural Computing and Applications | Ausgabe 7/2009

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Abstract

This work covers the problem of application of neural networks to recognition and categorization of non-fluent and fluent utterance records. Fifty-five 4-s speech samples where the blockade on plosives (p, b, t, d, k and g) occurred and 55 recordings of speech of fluent speakers containing the same fragments were applied. Two Kohonen networks were used. The purpose of the first network was to reduce the dimension of the vector describing the input signals. A result of the analysis was the output matrix consisting of the neurons winning in a particular time frame. This matrix was taken as an input for the next self-organizing map network. Various types of Kohonen networks were examined with respect to their ability to classify utterances correctly into two, non-fluent and fluent, groups. Good examination results were accomplished and classification correctness exceeded 76%.

Vorheriger Artikel Applying a novel decision rule to the sphere-structured support vector machines algorithm

Nächster Artikel A joint investigation of misclassification treatments and imbalanced datasets on neural network performance

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Titel: Speech nonfluency detection using Kohonen networks
verfasst von: Izabela Szczurowska
Wiesława Kuniszyk-Jóźkowiak
Elżbieta Smołka
Publikationsdatum: 01.10.2009
Verlag: Springer-Verlag
Erschienen in: Neural Computing and Applications / Ausgabe 7/2009
Print ISSN: 0941-0643
Elektronische ISSN: 1433-3058
DOI: https://doi.org/10.1007/s00521-009-0261-3

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