Speaker Recognition GMM Model Training
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Resource Overview
MATLAB implementation for GMM speaker recognition model training, requiring integration with Voicebox toolbox for MFCC feature extraction and k-means clustering initialization.
Detailed Documentation
This MATLAB program implements Gaussian Mixture Model (GMM) training for speaker recognition systems. The implementation relies on the Voicebox toolbox to perform critical preprocessing steps: Mel-Frequency Cepstral Coefficients (MFCC) extraction for feature representation and k-means clustering for initial parameter estimation. The training process involves Expectation-Maximization (EM) algorithm iterations to optimize GMM parameters, including mixture weights, means, and covariance matrices. This program enables the development of robust GMM speaker recognition models suitable for various speech processing applications, with proper configuration of parameters such as the number of Gaussian components and convergence thresholds.
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