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Speaker Normalization Improvement By Neural Network Parameter Optimization

Author

Listed:
  • MICHELE AUTIERO

    (IIASS "E. R. Caianiello", Vietri Sul Mare (SA), Italy)

  • DIEGO GIULIANI

    (IRST, Istituto per la Ricerca Scientifica e Tecnologica, Povo (TN), Italy)

  • SALVATORE RAMPONE

    (Facoltà di Scienze, Università del Sannio — Benevento, Via Port'Arsa 11, I-82100 Benevento, Italy)

  • ROBERTO TAGLIAFERRI

    (INFM, Unit of Salerno, Italy;
    DMI, Università di Salerno, Italy)

Abstract

In this work we investigate the use of a speaker adaptation technique, for speech recognition, based on neural network spectral mapping. Different multilayer perceptron neural network architectures are analyzed in order to optimize the spectral difference reduction in acoustic data of two speakers. Experiments are carried out in a telecontrol environment, used to provide voice commands to a mobile robot, based on DTW pattern matching.

Suggested Citation

  • Michele Autiero & Diego Giuliani & Salvatore Rampone & Roberto Tagliaferri, 1999. "Speaker Normalization Improvement By Neural Network Parameter Optimization," International Journal of Modern Physics C (IJMPC), World Scientific Publishing Co. Pte. Ltd., vol. 10(06), pages 1117-1135.
    • Handle: RePEc:wsi:ijmpcx:v:10:y:1999:i:06:n:s0129183199000917
    DOI: 10.1142/S0129183199000917
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