Regularization, adaptation, and non-independent features improve hidden conditional random fields for phone classification

2007 IEEE Workshop on Automatic Speech Recognition and Understanding, ASRU 2007, Proceedings

Volumn , Issue , 2007, Pages 347-352

  Sung, Yun Hsuan ^a   Boulis, Constantinos ^b   Manning, Christopher ^a,b   Jurafsky, Dan ^a,b  

^a Stanford University   (United States)

^b STANFORD UNIVERSITY   (United States)

Author keywords

A Posteriori; Hidden conditional; Maximum; Phone classification; Random fields; Speech recognition

Indexed keywords

CLASSIFICATION (OF INFORMATION); ELECTRIC SWITCHBOARDS; ERROR ANALYSIS; LEARNING SYSTEMS; MICROFLUIDICS; NEURAL NETWORKS; NUMERICAL METHODS; REUSABILITY; SOFTWARE AGENTS; SPEECH; SPEECH ANALYSIS; TELEPHONE SETS;

A POSTERIORI; AUTOMATIC SPEECH RECOGNITION (ASR); CLASSIFICATION ERROR RATE; CONDITIONAL RANDOM FIELD (CRF); CORPORA (CO); EARLY STOPPING; INDEPENDENCE (PERSONALITY); MIXTURE COMPONENTS; OVER-FITTING; SWITCHBOARD CORPUS;

SPEECH RECOGNITION;

EID: 44849143432     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: None     Document Type: Conference Paper

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