Means of Positive Numbers and Matrices
SIAM Journal on Matrix Analysis and Applications
Corpora for the evaluation of speaker recognition systems
ICASSP '99 Proceedings of the Acoustics, Speech, and Signal Processing, 1999. on 1999 IEEE International Conference - Volume 02
Integration of Stochastic Models by Minimizing α-Divergence
Neural Computation
MLP internal representation as discriminative features for improved speaker recognition
NOLISP'05 Proceedings of the 3rd international conference on Non-Linear Analyses and Algorithms for Speech Processing
α-Gaussian mixture modelling for speaker recognition
Pattern Recognition Letters
| Hi-index | 0.01 |
α-integration and α-GMM have been recently proposed for integrated stochastic modeling. However, there has not been an approach to date for estimating model parameters for α-GMM in a statistical way, based on a set of training data. In this letter, parameter updating formulas are mathematically derived based on maximum likelihood criterion using an adapted expectation-maximization algorithm. With this method, model parameters for α-GMM are reestimated in an iterative way. The updating formulas were found to be simple and systematically compatible with the GMM equations. This advantage renders the α-GMM a superset of the GMM but with similar computational complexity. This method has been effectively applied to realistic speaker recognition applications.