Wavelet Transform Based Consonant - Vowel (CV) Classification Using Support Vector Machines

  • T. M. Thasleema
  • N. K. Narayanan
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 7664)


This paper reports a study on static pattern classification technique using Support Vector Machine based Decision Directed Acyclic Graph (DDAG) algorithm for the classification of Malayalam Consonant – Vowel (CV) speech unit utterances. Wavelet Transform (WT) based Normalized Wavelet Hybrid Features (NWHF) by combining both Classical Wavelet Decomposition (CWD) and Wavelet Packet Decomposition (WPD) along with z – score normalization are used to evaluate the performance of the present classifier in speaker independent environment. From the experimental study it is reported that present DDAGSVM algorithms perform well for Malayalam CV speech unit recognition compared to ANN and k – NN in additive noisy condition.


Multi resolution analysis Normalized wavelet hybrid features Support vector machines Decision directed acyclic graph 


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Copyright information

© Springer-Verlag Berlin Heidelberg 2012

Authors and Affiliations

  • T. M. Thasleema
    • 1
  • N. K. Narayanan
    • 1
  1. 1.Dept. of Information TechnologyKannur UniveristyIndia

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