Wavelet Formants Speaker Identification Based System via Neural Network

نویسندگان

  • K. Daqrouq
  • Emad Khalaf
  • A. Al-Qawasmi
  • T. Abu Hilal
چکیده

In this paper Discrete wavelet Transform with logarithmic Power Spectrum Density (PSD) are combined for speaker formants extraction, to be used as evident classification features. For classification, Feed Forward Back Propagation Neural Network FFBNN method is proposed. The Discrete Wavelet formants Neural Network DWFNNT system works with excellent capability of features tracking even with 0dB SNR. Text dependant system is used, so that the system can be applied in password or PINs identification in any security system. The proposed system is compared with K-means algorithm based clustering method. The results show excellent performance with 93.21% Recognition Rate (RR).

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تاریخ انتشار 2009