Gaussian Mixture Models

@inproceedings{Reynolds2009GaussianMM,
  title={Gaussian Mixture Models},
  author={D. Reynolds},
  booktitle={Encyclopedia of Biometrics},
  year={2009}
}
  • D. Reynolds
  • Published in Encyclopedia of Biometrics 2009
  • Computer Science
Definition A Gaussian Mixture Model (GMM) is a parametric probability d ensity function represented as a weighted sum of Gaussian component densities. GMMs are commonly used as a parametric odel of the probability distribution of continuous measur ements or features in a biometric system, such as vocal-tract related spectral features in a speaker recognition system. GMM parameters are estimated from training data using the itera tiv Expectation-Maximization (EM) algorithm or Maximum A… Expand
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A Gaussian mixture modeling approach to text-independent speaker identification