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EFFICIENT DECODING WITH GENERATIVE SCORE-SPACES USING THE EXPECTATION SEMIRING Rogier C. van Dalen, Anton Ragni, and Mark J. F. Gales Department of Engineering University of Cambridge Cambridge, United Kingdom
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Document Date: 2013-03-25 11:19:17

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City

Helsinki / /

Country

Finland / /

Facility

Cambridge University / Engineering University of Cambridge Cambridge / /

IndustryTerm

speech recognition systems / automata algorithms / forward and backward algorithms / forward algorithm / dot product / forward algorithms / largevocabulary systems / backward algorithm / /

MusicAlbum

Speech / /

Organization

Cambridge University Engineering Department / Cambridge University / Engineering University of Cambridge Cambridge / Mark J. F. Gales Department / Association for Computational Linguistics / /

Person

Tommi Jaakkola / Sunita Sarawagi / Werner Kuich / Hirsch Pearce / Manfred Droste / Dan Gillick / Ralf Schl¨uter / Steven Wegmann / Anton Ragni / David Pearce / Georg Heigold / Larry Gillick / Zhifei Li / David Haussler / Thomas Deselaers / Jeffrey Mark Siskind / Heiko Vogler / Geoffrey Zweig / William W. Cohen / Martin Layton / Patrick Nguyen / Barak A. Pearlmutter / Hermann Ney / Jason Eisner / Mark J. F. Gales / /

Position

Fisher / forward / generative model for one segment / /

ProvinceOrState

AURORA / /

PublishedMedium

Computational Linguistics / Machine Learning / /

Technology

forward algorithm / Speech recognition / forward and backward algorithms / Inference algorithms / Natural Language Processing / decoding algorithm / Machine Learning / backward algorithm / two algorithms / /

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