This paper proposes to extend the band width of narrow band telephone speech signal by employing feed forward back propagation neural network. There are different types of faster training algorithm are available in the literature like Variable Learning Rate, Resilient Back propagation, Polak-Ribiére Conjugate Gradient , Conjugate Gradient with Powell/Beale Restarts , BFGS Quasi-Newton , One-Step Secant , FletcherPowell Conjugate Gradient Algorithms, Scaled Conjugate Gradient and Liebenberg-Marquardt. These algorithms are used to train the BPN networks using Neural network tool box. The correlation between the inputs of the neural network and the input-output correlation were calculated. The components were employed to reconstruct the speech signal and the results are analyzed.
General TermsArtificial band width expansion, Signal processing, Neural networks , Training algorithm .
KeywordsAR Filter, Back propagation neural network , linear mapping method, code book method.
In this paper, we are estimating the pitch of telephone speech signal. We use different types of methods such us, Burg, Covariance, Fast Fourier transform, Modified Covariance, Multiple Signal Classification (MUSIC) algorithm or Eigen vector, Multi Taper method (MTM), Welch, and Yule Auto Regressive (Yule AR) , to estimate the PSD using signal processing tool box of MATLAB. The spectrum was constructed and the pitch ,amplitude , and slope of the speech signal were calculated and their performance were analyzed.
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