UNDERSTANDING HOW DEEP BELIEF NETWORKS PERFORM ACOUSTIC MODELLING Abdel-rahman Mohamed, Geoffrey Hinton, and Gerald Penn Department of Computer Science, University of Toronto ABSTRACT Deep Belief Networks (DBNs) are a ve - Deep learning - Document - PDFSEARCH.IO

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	UNDERSTANDING HOW DEEP BELIEF NETWORKS PERFORM ACOUSTIC MODELLING Abdel-rahman Mohamed, Geoffrey Hinton, and Gerald Penn Department of Computer Science, University of Toronto ABSTRACT Deep Belief Networks (DBNs) are a ve Add to Reading List Document Date: 2012-09-17 19:52:25 Open Document File Size: 1,05 MB Share Result on Facebook Company ABSTRACT Deep Belief Networks / MFCCs / / Facility University of Toronto ABSTRACT Deep Belief Networks / / IndustryTerm neural networks / iterative search / shallow network / belief networks / deep belief networks / neural network / hidden-layer neural networks / feedforward neural networks / filter-bank features / learning algorithm / feedforward neural network / transform-based log filter-bank / energy / multi-layer neural network / / MarketIndex SET 50 / / MusicAlbum Speech / / Organization Gerald Penn Department of Computer Science / University of Toronto ABSTRACT Deep Belief Networks / / Person Geoffrey Hinton / Gerald Penn / / Position speaker / / PublishedMedium Journal of Machine Learning Research / / Technology speech recognition / Machine Learning / neural network / / SocialTag Applied mathematics Speech recognition Mel-frequency cepstrum Supervised learning Feedforward neural network Backpropagation Discrete cosine transform Neural networks Cybernetics Science

UNDERSTANDING HOW DEEP BELIEF NETWORKS PERFORM ACOUSTIC MODELLING Abdel-rahman Mohamed, Geoffrey Hinton, and Gerald Penn Department of Computer Science, University of Toronto ABSTRACT Deep Belief Networks (DBNs) are a veAdd to Reading List