Tree-based Gaussian mixture models for speaker verification
Thesis (MScEng (Electrical and Electronic Engineering))--University of Stellenbosch, 2005.
The Gaussian mixture model (GMM) performs very effectively in applications such as speech and speaker recognition. However, evaluation speed is greatly reduced when the GMM has a large number of mixture components. Various techniques improve the evaluation speed by reducing the number of required Gaussian evaluations.