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Kernel Springy Discriminant Analysis and Its Application to a Phonological Awareness Teaching System

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Text, Speech and Dialogue (TSD 2002)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 2448))

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Abstract

Making use of the ubiquitous kernel notion, we present a new nonlinear supervised feature extraction technique called Kernel Springy Discriminant Analysis. We demonstrate that this method can efficiently reduce the number of features and increase classification performance. The improvements obtained admittedly arise from the nonlinear nature of the extraction technique developed here. Since phonological awareness is a great importance in learning to read, a computer-aided training system could be most beneficial in teaching young learners. Naturally, our system employs an effective automatic phoneme recognizer based on the proposed feature extraction technique.

This work was supported under the contract IKTA No. 2001/055 from the Hungarian Ministry of Education.

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References

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Authors and Affiliations

  1. Research Group on Artificial Intelligence of the Hungarian Academy of Sciences, Aradi vértanúk tere 1., H-6720, Szeged, Hungary

    András Kocsor

  2. University of Szeged, Aradi vértanúk tere 1., H-6720, Szeged, Hungary

    Kornél Kovács

Authors
  1. András Kocsor
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  2. Kornél Kovács
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Editor information

Editors and Affiliations

  1. Faculty of Informatics Department of Programming Systems and Communication, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Petr Sojka

  2. Faculty of Informatics Department of Information Technologies, Masaryk University, Botanická 68a, 602 00, Brno, Czech Republic

    Ivan Kopeček  & Karel Pala  & 

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© 2002 Springer-Verlag Berlin Heidelberg

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Kocsor, A., Kovács, K. (2002). Kernel Springy Discriminant Analysis and Its Application to a Phonological Awareness Teaching System. In: Sojka, P., Kopeček, I., Pala, K. (eds) Text, Speech and Dialogue. TSD 2002. Lecture Notes in Computer Science(), vol 2448. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-46154-X_45

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  • DOI: https://doi.org/10.1007/3-540-46154-X_45

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-44129-8

  • Online ISBN: 978-3-540-46154-8

  • eBook Packages: Springer Book Archive

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