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» Hierarchical Gaussian process latent variable models
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ICASSP
2010
IEEE
15 years 6 months ago
Under-determined convolutive blind source separation using spatial covariance models
This paper deals with the problem of under-determined convolutive blind source separation. We model the contribution of each source to all mixture channels in the time-frequency d...
Ngoc Q. K. Duong, Emmanuel Vincent, Rémi Gr...
JCB
2007
198views more  JCB 2007»
15 years 6 months ago
Bayesian Hierarchical Model for Large-Scale Covariance Matrix Estimation
Many bioinformatics problems can implicitly depend on estimating large-scale covariance matrix. The traditional approaches tend to give rise to high variance and low accuracy esti...
Dongxiao Zhu, Alfred O. Hero III
ICASSP
2011
IEEE
14 years 10 months ago
Learning vocal tract variables with multi-task kernels
The problem of acoustic-to-articulatory speech inversion continues to be a challenging research problem which significantly impacts automatic speech recognition robustness and ac...
Hachem Kadri, Emmanuel Duflos, Philippe Preux
ICIP
2008
IEEE
16 years 8 months ago
Variational Bayesian image processing on stochastic factor graphs
In this paper, we present a patch-based variational Bayesian framework of image processing using the language of factor graphs (FGs). The variable and factor nodes of FGs represen...
Xin Li
ICASSP
2011
IEEE
14 years 10 months ago
Joint Bayesian removal of impulse and background noise
We present a method for the removal of noise including nonGaussian impulses from a signal. Impulse noise is removed jointly a homogenous Gaussian noise floor using a Gabor regres...
James Murphy, Simon J. Godsill