• DocumentCode
    2744865
  • Title

    Isolated spoken number recognition with hybrid of self-organizing map and multilayer perceptron

  • Author

    Salmela, Petri ; Laurila, Kari ; Kuusisto, Seppo ; Haavisto, Petri ; Saarinen, Jukka

  • Author_Institution
    Electron. Lab., Tampere Univ. of Technol., Finland
  • Volume
    4
  • fYear
    1996
  • fDate
    3-6 Jun 1996
  • Firstpage
    1912
  • Abstract
    A neural network, which is capable of recognizing isolated spoken numbers speaker independently is described. The recognition system is a hybrid of a self-organizing map (SOM) and a multilayer perceptron (MLP). The SOM maps the feature vectors of a word in a constant dimension binary matrix, which is classified by a MLP. The decision borders of the SOM were fine-tuned with the LVQ1 algorithm, with which the hybrid achieved over 99% recognition out of 1232 test set samples. The training convergence of the MLP was tested with two different initialization methods
  • Keywords
    convergence; learning (artificial intelligence); multilayer perceptrons; self-organising feature maps; speech recognition; vector quantisation; LVQ1 algorithm; constant dimension binary matrix; decision borders; hybrid self-organizing map/multilayer perceptron; initialization methods; isolated spoken number recognition; training convergence; Commercialization; Isolation technology; Laboratories; Linear discriminant analysis; Mood; Multilayer perceptrons; Neural networks; Neurons; Speech recognition; Testing;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Neural Networks, 1996., IEEE International Conference on
  • Conference_Location
    Washington, DC
  • Print_ISBN
    0-7803-3210-5
  • Type

    conf

  • DOI
    10.1109/ICNN.1996.549193
  • Filename
    549193