Maximum likelihood clustering of Gaussians for speech recognition

Describes a method for clustering multivariate Gaussian distributions using a maximum likelihood criterion. The authors point out possible applications of model clustering, and then use the approach to determine classes of shared covariances for contest modeling in speech recognition, achieving an order of magnitude reduction in the number of covariance parameters, with no loss in recognition performance. >

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