Tree-based Gaussian mixture models for speaker verification

Cilliers, Francois Dirk (2005-12)

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.

Please refer to this item in SUNScholar by using the following persistent URL:
This item appears in the following collections: