.: Click here to download :.
Extraction and selection of the best parametric representation of acoustic signal is the most
important task in designing any speaker recognition system. A wide range of possibilities exists
for parametrically representing the speech signal such as Linear Prediction Coding (LPC) ,Mel
frequency Cepstrum coefficients (MFCC) and others. MFCC are currently the most popular
choice for any speaker recognition system, though one of the shortcomings of MFCC is that the
signal is assumed to be stationary within the given time frame and is therefore unable to analyze
the non-stationary signal. Therefore it is not suitable for noisy speech signals. To overcome this
problem several researchers used different types of AM-FM modulation/demodulation techniques
for extracting features from speech signal. In some approaches it is proposed to use the wavelet
filterbanks for extracting the features. We have developed a fast and reliable algorithm for text independent speaker recognition.
Features are extracted from the signal through wavelet filterbank. It is found that the proposed
method outperforms the existing feature extraction techniques.
Index Terms: Matlab, source, code, speaker, recognition, matching, discrete, wavelet, transform, DWT, text, independent.
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Figure 1. Text independent speaker recognition |
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A simple and effective source code for Wavelet Speaker Recognition. |
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Demo code (protected
P-files) available for performance evaluation. Matlab and Matlab Wavelet Toolbox are required.
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Release |
Date |
Major features |
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1.0 |
2013.02.26 |
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We recommend to check the secure connection to PayPal, in order to avoid any fraud. This donation has to be considered an encouragement to improve the code itself. |
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Wavelet Speaker Recognition. Click here for
your donation. In order to obtain the source code you
have to pay a little sum of money: 600 EUROS (less
than 840 U.S. Dollars). |
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Once you have done this, please email us luigi.rosa@tiscali.it As soon as possible (in a few days) you will receive our new release of Wavelet Speaker Recognition. Alternatively, you can bestow using our banking coordinates:
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The authors have no relationship or partnership
with The Mathworks. All the code provided is written in Matlab
language (M-files and/or M-functions), with no dll or other
protected parts of code (P-files or executables). The code was
developed with Matlab 14 SP1. Matlab and Matlab Wavelet Toolbox are required.
The code provided has to be considered "as is" and it is without any kind of warranty. The
authors deny any kind of warranty concerning the code as well
as any kind of responsibility for problems and damages which may
be caused by the use of the code itself including all parts of
the source code.
