DocumentCode :
3224254
Title :
Speaker identification system using Wavelet Transform and neural network
Author :
Daqrouq, K. ; Abu Hilal, T. ; Sherif, M. ; El-Hajjar, S. ; Al-Qawasmi, A.
Author_Institution :
Philadelphia Univ., Amman, Jordan
fYear :
2009
fDate :
15-17 July 2009
Firstpage :
559
Lastpage :
564
Abstract :
The speech enhancement that is concerned with the processing of corrupted or noisy speech signal in order to improve the quality of speaker recognition system is presented. This idea of noise cancellation for the speech signal is processed to increase the speaker recognition system robustness. The presented system is divided into two blocks: 1. Discrete Wavelet Transform DWT and Adaptive Linear Neuron (Adaline) Enhancement Method (DWADE). 2. Wavelet Gender Discrimination (WGD) and Speaker Recognition using Discrete Wavelet Transform (DWT) Power Spectrum Density (PSD). The tested signal is enhanced up to 15 dB by Wavelet Transform and Adaline Enhancement Method that increases the speaker recognition rate. The accomplished speaker recognition rate is about 95%. Back Propagation Feed Forward Neural Network (BPFFNN) perceptron classification methods are used.
Keywords :
backpropagation; discrete wavelet transforms; feedforward neural nets; pattern classification; speaker recognition; speech enhancement; Adaline enhancement method; adaptive linear neuron enhancement method; backpropagation feed forward neural network perceptron classification; discrete wavelet transform; noisy speech signal; power spectrum density; speaker identification system; speaker recognition rate; speech enhancement; wavelet gender discrimination; Discrete wavelet transforms; Neural networks; Neurons; Noise cancellation; Noise robustness; Signal processing; Speaker recognition; Speech enhancement; Speech processing; Wavelet transforms;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Advances in Computational Tools for Engineering Applications, 2009. ACTEA '09. International Conference on
Conference_Location :
Zouk Mosbeh
Print_ISBN :
978-1-4244-3833-4
Electronic_ISBN :
978-1-4244-3834-1
Type :
conf
DOI :
10.1109/ACTEA.2009.5227953
Filename :
5227953
Link To Document :
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