• DocumentCode
    351255
  • Title

    Speaker identification using a combination of different parameters as feature inputs to an artificial neural network classifier

  • Author

    Moonasar, Viresh ; Venayagamoorthy, Ganesh K.

  • Author_Institution
    Dept. of Electron. Eng., ML Sultan Technikon, Durban, South Africa
  • Volume
    1
  • fYear
    1999
  • fDate
    1999
  • Firstpage
    189
  • Abstract
    This paper presents a technique using artificial neural networks (ANNs) for speaker identification that results in a better success rate compared to other techniques. The technique used in this paper uses both power spectral densities (PSDs) and linear prediction coefficients (LPCs) as feature inputs to a self organizing feature map to achieve a better identification performance. Results for speaker identification with different methods are presented and compared
  • Keywords
    pattern classification; prediction theory; self-organising feature maps; speaker recognition; spectral analysis; ANN; artificial neural network classifier; feature inputs; identification performance; linear prediction coefficients; power spectral densities; self organizing feature map; speaker identification; success rate; Africa; Artificial neural networks; Biometrics; Feature extraction; Linear predictive coding; Organizing; Power engineering and energy; Signal processing; Speaker recognition; Speech;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Africon, 1999 IEEE
  • Conference_Location
    Cape Town
  • Print_ISBN
    0-7803-5546-6
  • Type

    conf

  • DOI
    10.1109/AFRCON.1999.820791
  • Filename
    820791