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» Combining Gaussian Mixture Models
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ICPR
2008
IEEE
14 years 2 months ago
Parameter-based reduction of Gaussian mixture models with a variational-Bayes approach
This paper 1 proposes a technique for simplifying a given Gaussian mixture model, i.e. reformulating the density in a more parcimonious manner, if possible (less Gaussian componen...
Pierrick Bruneau, Marc Gelgon, Fabien Picarougne
ICASSP
2011
IEEE
12 years 11 months ago
Structured precision modelling with Cholesky Basis Superposition for speech recognition
Structured precision modelling is an important approach to improve the intra-frame correlation modelling of the standard HMM, where Gaussian mixture model with diagonal covariance...
Lei Jia, Kai Yu, Bo Xu
FOCS
1999
IEEE
13 years 12 months ago
Learning Mixtures of Gaussians
Mixtures of Gaussians are among the most fundamental and widely used statistical models. Current techniques for learning such mixtures from data are local search heuristics with w...
Sanjoy Dasgupta
NIPS
2003
13 years 9 months ago
Gene Expression Clustering with Functional Mixture Models
We propose a functional mixture model for simultaneous clustering and alignment of sets of curves measured on a discrete time grid. The model is specifically tailored to gene exp...
Darya Chudova, Christopher E. Hart, Eric Mjolsness...
ICASSP
2010
IEEE
13 years 7 months ago
Subspace Gaussian Mixture Models for speech recognition
We describe an acoustic modeling approach in which all phonetic states share a common Gaussian Mixture Model structure, and the means and mixture weights vary in a subspace of the...
Daniel Povey, Lukas Burget, Mohit Agarwal, Pinar A...