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Econometrics / Machine learning / Markov models / Hidden Markov model / Maximum likelihood / Linear regression / Pattern recognition / Normal distribution / Conditional random field / Statistics / Estimation theory / Regression analysis


MAXIMUM CONDITIONAL LIKELIHOOD LINEAR REGRESSION AND MAXIMUM A POSTERIORI FOR HIDDEN CONDITIONAL RANDOM FIELDS SPEAKER ADAPTATION Yun-Hsuan Sung,1 Constantinos Boulis,2 Dan Jurafsky3 Electrical Engineering,1 Linguistics2
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Document Date: 2008-04-28 14:26:34

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City

Columbus / /

Company

AUAI Press / CRFs / S. Wang L.P. / /

Country

United States / /

Facility

Ohio State University / /

IndustryTerm

line search / /

MarketIndex

ABSTRACT / /

Movie

Regularization / /

MusicGroup

Entropy / /

Organization

Ohio State University / Department of Psychology / MLLR HMM / MCLLR MAP / Stanford University Stanford / Pattern Analysis and Machine Intelligence / /

Person

Chris Manning / William Byrne / Yun-Hsuan Sung / A. Gunawardana / /

Position

speaker independent model / i.e / testing speaker / Speaker / / training speaker / /

ProvinceOrState

Ohio / /

PublishedMedium

IEEE Transactions on Pattern Analysis and Machine Intelligence / /

Technology

speech recognition / gesture recognition / MLLR algorithm / /

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