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Perceptual Linear Predictive Cepstral Coefficient for Malayalam Isolated Digit Recognition

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Trends in Computer Science, Engineering and Information Technology (CCSEIT 2011)

Part of the book series: Communications in Computer and Information Science ((CCIS,volume 204))

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Abstract

This paper presents an optimum speaker independent isolated digit recognizer for Malayalam language. The system employs Perceptual Linear Predictive (PLP) cepstral coefficient for speech parameterization. The powerful and well accepted pattern recognition technique Hidden Markov Model is used for acoustic modeling. The training data base has the utterance of 21 speakers from the age group ranging from 20 to 40 years and the sound is recorded in the normal office environment where each speaker uttered digits zero to nine independently. The system obtained an accuracy of 99.5% with the unseen data.

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Author information

Authors and Affiliations

  1. Department of Computer Applications, Cochin University of Science & Technology, Cochin, 682 022, India

    Cini Kurian & Kannan Balakrishnan

Authors
  1. Cini Kurian
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  2. Kannan Balakrishnan
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Editor information

Editors and Affiliations

  1. Wireilla Net Solutions PTY Ltd, Melbourne, Victoria, Australia

    Dhinaharan Nagamalai

  2. Institut Telecom/Telecom SudParis, 91011, 9, rue Charles Fourier, Evry Cedex, France

    Eric Renault

  3. Manonmaniam Sundaranar University, Thirunelveli, Tamil Nadu, India

    Murugan Dhanuskodi

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© 2011 Springer-Verlag Berlin Heidelberg

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Kurian, C., Balakrishnan, K. (2011). Perceptual Linear Predictive Cepstral Coefficient for Malayalam Isolated Digit Recognition. In: Nagamalai, D., Renault, E., Dhanuskodi, M. (eds) Trends in Computer Science, Engineering and Information Technology. CCSEIT 2011. Communications in Computer and Information Science, vol 204. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-24043-0_54

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  • DOI: https://doi.org/10.1007/978-3-642-24043-0_54

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-642-24042-3

  • Online ISBN: 978-3-642-24043-0

  • eBook Packages: Computer ScienceComputer Science (R0)

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