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How to Reduce Dimension while Improving Performance

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Hybrid Artificial Intelligent Systems (HAIS 2012)

Part of the book series: Lecture Notes in Computer Science ((LNAI,volume 7208))

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Abstract

This paper addresses the feature subset selection for an automatic Arabic speaker recognition system. An effective algorithm based on genetic algorithm is proposed for discovering the best feature combinations using feature reduction and recognition error rate as performance measure. Experimentation is carried out using QSDAS corpora. The results of experiments indicate that, with the optimized feature subset, the performance of the system is improved. Moreover, the speed of recognition is significantly increased, number of features is reduced over 60% which consequently decrease the complexity of our ASR system

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Author information

Authors and Affiliations

  1. Department of Electronics, Faculty of Technology, University Mohamed Boudiaf Msila, BP 166, Ichbilia, 28000, Algeria

    Abdelghani Harrag, D. Saigaa, A. Bouchelaghem, M. Drif & S. Zeghlache

  2. Department of Informatics, Faculty of Sciences, University Ferhat Abbas Setif, El-Baz, 19000, Setif, Algeria

    N. Harrag

Authors
  1. Abdelghani Harrag
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  2. D. Saigaa
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  3. A. Bouchelaghem
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  4. M. Drif
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  5. S. Zeghlache
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  6. N. Harrag
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Editor information

Editors and Affiliations

  1. Universidad de Salamanca, Plaza de la Merced S/N, 37008, Salamanca, Spain

    Emilio Corchado

  2. VÅ B-TU Ostrava 17, Listopadu 15, 70833, Ostrava, Czech Republic

    Václav Snášel

  3. Machine Intelligence Research Labs(MIR Labs), Scientific Network for Innovation and Research Excellence, P.O. Box 2259, 98071, Auburn, Washington, USA

    Ajith Abraham

  4. Wroclaw University of Technology, Wybrzeze Wyspianskiego 27, 50-370, Wroclaw, Poland

    Michał Woźniak

  5. University of the Basque Country, Pº Manuel Lardizabal 1, 20018, San Sebastian, Spain

    Manuel Graña

  6. Yonsei University, 134 Shinchon-dong, Sudaemoon-ku, 120-749, Seoul, Korea

    Sung-Bae Cho

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© 2012 Springer-Verlag Berlin Heidelberg

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Harrag, A., Saigaa, D., Bouchelaghem, A., Drif, M., Zeghlache, S., Harrag, N. (2012). How to Reduce Dimension while Improving Performance. In: Corchado, E., Snášel, V., Abraham, A., Woźniak, M., Graña, M., Cho, SB. (eds) Hybrid Artificial Intelligent Systems. HAIS 2012. Lecture Notes in Computer Science(), vol 7208. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-28942-2_45

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  • DOI: https://doi.org/10.1007/978-3-642-28942-2_45

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-28941-5

  • Online ISBN: 978-3-642-28942-2

  • eBook Packages: Computer ScienceComputer Science (R0)

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