Speaker Recognition: a Biometric-based Personal Identification Technology

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Speaker Recognition

Speaker Recognition System

Speaker Recognition Based on Neural Networks

Radon Transform Speaker Recognition

Wavelet Speaker Recognition

Speaker Verification System

RASTA-PLP Speaker Identification

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Wavelet Speaker Recognition


Download now Matlab source code
Requirements: Matlab, Matlab Wavelet Toolbox.

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.

Release 1.0 Date 2013.02.26
Major features:


Speaker Recognition . It Luigi Rosa mobile +39 3207214179 luigi.rosa@tiscali.it
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