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» Hierarchical Gaussian Mixture Model
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147
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ICCV
2007
IEEE
16 years 5 months ago
Robust Image Registration using Mixtures of t-distributions
We propose a pixel similarity-based algorithm enabling accurate rigid registration between single and multimodal images presenting gross dissimilarities due to noise, missing data...
Demetrios Gerogiannis, Christophoros Nikou, Aristi...
133
Voted
ICASSP
2011
IEEE
14 years 7 months ago
Non-parallel training for voice conversion based on FT-GMM
This paper presents a non-parallel training algorithm for voice conversion based on feature transform Gaussian mixture model (FTGMM), which is a mixture model of joint density spa...
Ling-Hui Chen, Zhen-Hua Ling, Li-Rong Dai
113
Voted
ICASSP
2008
IEEE
15 years 10 months ago
Towards the use of full covariance models for missing data speaker recognition
This work investigates the use of missing data techniques for noise robust speaker identification. Most previous work in this field relies on the diagonal covariance assumption ...
Marco Kühne, Daniel Pullella, Roberto Togneri...
124
Voted
ICASSP
2009
IEEE
15 years 10 months ago
Interpolating hidden Markov model and its application to automatic instrument recognition
This paper proposes an interpolating extension to hidden Markov models (HMMs), which allows more accurate modeling of natural sounds sources. The model is able to produce observat...
Tuomas Virtanen, Toni Heittola
135
Voted
NIPS
2004
15 years 5 months ago
Spike Sorting: Bayesian Clustering of Non-Stationary Data
Spike sorting involves clustering spike trains recorded by a microelectrode according to the source neuron. It is a complicated problem, which requires a lot of human labor, partl...
Aharon Bar-Hillel, Adam Spiro, Eran Stark