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Science / Boltzmann machine / Speech recognition / Backpropagation / Hidden Markov model / Feedforward neural network / Pattern recognition / Markov chain / DBN / Neural networks / Statistics / Machine learning


Deep Belief Networks for phone recognition Abdel-rahman Mohamed, George Dahl, and Geoffrey Hinton Department of Computer Science University of Toronto {asamir,gdahl,hinton}@cs.toronto.edu
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Document Date: 2009-11-25 20:25:23

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Deep Belief Networks / Neural Information Processing Systems / Neural Networks / Monte Carlo / using Deep Belief Networks (DBNs) / /

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Facility

University of Toronto / Computer Science University of Toronto / /

IndustryTerm

energy function / layer network / deeper belief networks / graphics processor / belief networks / greedy layer-wise unsupervised learning algorithm / run using grid search / much deeper belief networks / dynamical systems / learning algorithm / energy / /

MarketIndex

SET 50 / /

MusicAlbum

Speech / /

Organization

Department of Computer Science / US Federal Reserve / Geoffrey Hinton Department / Acoustical Society of America / University of Toronto / /

Person

Thomas G. Dietterich / Simon King / Volodymyr Mnih / Ruslan Salakhutdinov / Geoffrey E. Hinton / Pavel Matjka / Petr Schwarz / Geoffrey Hinton / Li Deng / James R. Glass / Alexander Gutkin / UTML TR / Radford M. Neal / Dong Yu / Ghulum Bakiri / A. Acero / George Dahl / /

Position

general types / speaker / /

PublishedMedium

Journal of Artificial Intelligence Research / /

Technology

Speech Recognition / neural network / 3-D / greedy layer-wise unsupervised learning algorithm / graphics processor / Machine Translation / data modeling / GSM / machine learning / /

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http /

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