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» Subspace Gaussian Mixture Models for speech recognition
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CVPR
2012
IEEE
13 years 2 days ago
Robust Boltzmann Machines for recognition and denoising
While Boltzmann Machines have been successful at unsupervised learning and density modeling of images and speech data, they can be very sensitive to noise in the data. In this pap...
Yichuan Tang, Ruslan Salakhutdinov, Geoffrey E. Hi...
ICML
2009
IEEE
15 years 10 months ago
Matrix updates for perceptron training of continuous density hidden Markov models
In this paper, we investigate a simple, mistakedriven learning algorithm for discriminative training of continuous density hidden Markov models (CD-HMMs). Most CD-HMMs for automat...
Chih-Chieh Cheng, Fei Sha, Lawrence K. Saul
94
Voted
NIPS
2004
14 years 11 months ago
A Three Tiered Approach for Articulated Object Action Modeling and Recognition
Visual action recognition is an important problem in computer vision. In this paper, we propose a new method to probabilistically model and recognize actions of articulated object...
Le Lu, Gregory D. Hager, Laurent Younes
FGR
2000
IEEE
181views Biometrics» more  FGR 2000»
15 years 2 months ago
Face Detection Using Mixtures of Linear Subspaces
We present two methods using mixtures of linear subspaces for face detection in gray level images. One method uses a mixture of factor analyzers to concurrently perform clustering...
Ming-Hsuan Yang, Narendra Ahuja, David J. Kriegman
77
Voted
NAACL
2003
14 years 11 months ago
Getting More Mileage from Web Text Sources for Conversational Speech Language Modeling using Class-Dependent Mixtures
Sources of training data suitable for language modeling of conversational speech are limited. In this paper, we show how training data can be supplemented with text from the web ï...
Ivan Bulyko, Mari Ostendorf, Andreas Stolcke