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» Hierarchical Gaussian process latent variable models
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ICASSP
2010
IEEE
14 years 12 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...
115
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JCB
2007
198views more  JCB 2007»
14 years 11 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 3 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 1 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 3 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