Are Sparse Representations Rich Enough for Acoustic Modeling? Oriol Vinyals1 , Li Deng2 1 University of California at Berkeley (Berkeley, CA, US) 2 - Matching pursuit - Document - PDFSEARCH.IO

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	Are Sparse Representations Rich Enough for Acoustic Modeling? Oriol Vinyals1 , Li Deng2 1 University of California at Berkeley (Berkeley, CA, US) 2 Add to Reading List Document Date: 2012-08-20 14:23:22 Open Document File Size: 100,53 KB Share Result on Facebook City Exemplar / / Company Deep Neural Networks / Microsoft / / Country United States / / / Facility University of California at Berkeley / / IndustryTerm neural networks / Speech processing / neural network / convex network / inner product / kmeans algorithm / energy distribution / / MusicAlbum Speech / / Organization University of California / / Person Yuanqing Lin / M. Elhilali / T.D. Tran / S.K. Nemala / Suman Ravuri / Nelson Morgan / G. Sivaram / H. Hermansky / Kai Yu / / ProgrammingLanguage C / / ProvinceOrState California / / RadioStation Core / / Technology neuroscience / speech recognition / kmeans algorithm / machine learning / neural network / / URL http / SocialTag Signal processing Cybernetics Learning Regression analysis Support vector machine Linear classifier Matching pursuit Sparse matrix Compressed sensing Statistics

Are Sparse Representations Rich Enough for Acoustic Modeling? Oriol Vinyals1 , Li Deng2 1 University of California at Berkeley (Berkeley, CA, US) 2Add to Reading List