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» Combining Gaussian Mixture Models
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CSL
2004
Springer
13 years 8 months ago
Factor analysed hidden Markov models for speech recognition
Recently various techniques to improve the correlation model of feature vector elements in speech recognition systems have been proposed. Such techniques include semi-tied covaria...
Antti-Veikko I. Rosti, M. J. F. Gales
TIP
2010
167views more  TIP 2010»
13 years 3 months ago
A Bayesian Framework for Image Segmentation With Spatially Varying Mixtures
Abstract--A new Bayesian model is proposed for image segmentation based upon Gaussian mixture models (GMM) with spatial smoothness constraints. This model exploits the Dirichlet co...
Christophoros Nikou, Aristidis Likas, Nikolas P. G...
ISCAS
2005
IEEE
214views Hardware» more  ISCAS 2005»
14 years 2 months ago
Blind separation of statistically independent signals with mixed sub-Gaussian and super-Gaussian probability distributions
— In the context of Independent Component Analysis (ICA), we propose a simple method for online estimation of activation functions in order to blindly separate instantaneous mixt...
Muhammad Tufail, Masahide Abe, Masayuki Kawamata
ICASSP
2011
IEEE
13 years 21 days ago
High accurate model-integration-based voice conversion using dynamic features and model structure optimization
This paper combines a parameter generation algorithm and a model optimization approach with the model-integration-based voice conversion (MIVC). We have proposed probabilistic int...
Daisuke Saito, Shinji Watanabe, Atsushi Nakamura, ...
BC
2002
91views more  BC 2002»
13 years 8 months ago
Linear combinations of nonlinear models for predicting human-machine interface forces
ACT This study presents a computational framework that capitalizes on known human neuromechanical characteristics during limb movements in order to predict man-machine interactions...
James L. Patton, Ferdinando A. Mussa-Ivaldi