A Model-Selection-Based Self-Splitting Gaussian Mixture Learning with Application to Speaker Identification

A Model-Selection-Based Self-Splitting Gaussian Mixture Learning with Application to Speaker Identification

We propose a self-splitting Gaussian mixture learning (SGML) algorithm for Gaussian mixture modelling. The SGML algorithm is deterministic and is able to find an appropriate number of components of the Gaussian mixture model (GMM) based on a self-splitting validity measure, Bayesian information crit...

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Bibliographic Details
Main Authors: Shih-Sian Cheng, Hsin-Chia Fu, Hsin-Min Wang
Format: Article
Language:English
Published: SpringerOpen 2004-12-01
Series:EURASIP Journal on Advances in Signal Processing
Subjects:
unsupervised learning
Gaussian mixture modelling
Bayesian information criterion
speaker identification.
Online Access:http://dx.doi.org/10.1155/S1110865704407100

Internet

http://dx.doi.org/10.1155/S1110865704407100

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