Maximizing global entropy reduction for active learning in speech recognition

ICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings

Volumn , Issue , 2009, Pages 4721-4724

  Varadarajan, Balakrishnan ^a   Yu, Dong ^b   Deng, Li ^b   Acero, Alex ^b  

^a JOHNS HOPKINS UNIVERSITY   (United States)

^b MICROSOFT RESEARCH   (United States)

Author keywords

Acoustic model; Active learning; Confidence; Entropy; Lattice

Indexed keywords

ACOUSTIC MODEL; ACTIVE LEARNING; ACTIVE-LEARNING ALGORITHM; AUTOMATIC SPEECH RECOGNITION SYSTEM; CONFIDENCE; DATA SETS; GLOBAL ENTROPY; LATTICE; LATTICE ENTROPY; RANDOM SAMPLING; RECOGNITION ACCURACY; USAGE SCENARIOS;

ACOUSTICS; EDUCATION; ENTROPY; LEARNING ALGORITHMS; SIGNAL PROCESSING; TRANSCRIPTION;

SPEECH RECOGNITION;

EID: 70349210856     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2009.4960685     Document Type: Conference Paper

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