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CONTEXT DEPENDENT RECURRENT NEURAL NETWORK LANGUAGE MODEL Tomas Mikolov ∗ Geoffrey Zweig BRNO University of Technology
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Document Date: 2012-10-05 16:12:59

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Company

Wall Street Journal / Neural Networks / Learning Recurrent Neural Networks / Treebank / Penn Treebank / RNN LDA / Microsoft / /

Country

Espana / /

Facility

Brno University of Technology / Geoffrey Zweig BRNO University of Technology Czech Republic Microsoft Research Redmond / /

IndustryTerm

voice-search application / voice-search setting / important / learning algorithm / voice search / /

MusicAlbum

Speech / /

Organization

Brno University of Technology / Geoffrey Zweig BRNO University of Technology Czech Republic Microsoft Research Redmond / American Society for Information Science / Pattern Analysis and Machine Intelligence / /

Person

Stefan Kombrink / Holger Schwenk / Sanjeev Khudanpur / Lukas Burget / Daniel Povey / Francois Yvon / Hai Son / Tomas Mikolov / Mary Ann Marcinkiewicz / Andrew Y. Ng / Ahmad Emami / Michael I. Jordan / Jun Wu / Peng Xu / Mitchell P. Marcus / Patrice Simard / Geoffrey Hinton / Frederick Jelinek / Jan Cernocky / Hai-Son Le / Geoffrey Zweig / Mary Harper / Denis Filimonov / Yoshua Bengio / Anoop Deoras / Beatrice Santorini / Alexandre Allauzen / Martin Karafiat / David M. Blei / Paolo Frasconi / Andriy Mnih / /

Position

CONTEXT DEPENDENT RECURRENT NEURAL NETWORK LANGUAGE MODEL / speaker / classical feed-forward / joint language model / Linguist / /

PublishedMedium

the Wall Street Journal / Machine Learning / Wall Street Journal / /

Technology

learning algorithm / speech recognition / NEURAL NETWORK / machine translation / http / Machine Learning / /

URL

www.cs.princeton.edu/∼blei/lda-c / /

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