Subspace gaussian mixture models for speech recognition

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

Volumn , Issue , 2010, Pages 4330-4333

  Povey, Daniel ^a   Burget, Lukáš ^b   Agarwal, Mohit ^c   Akyazi, Pinar ^d   Feng, Kai ^e   Ghoshal, Arnab ^f   Glembek, Ondřej ^b   Goel, Nagendra Kumar ^g   Karafiát, Martin ^b   Rastrow, Ariya ^h   Rose, Richard C ⁱ   Schwarz, Petr ^b   Thomas, Samuel ^h  

^a MICROSOFT RESEARCH   (United States)

^b BRNO UNIVERSITY OF TECHNOLOGY   (Czech Republic)

^c INDIAN INSTITUTE OF INFORMATION TECHNOLOGY   (India)

^d BOGAZICI UNIVERSITY   (Turkey)

^e HONG KONG UNIVERSITY OF SCIENCE AND TECHNOLOGY   (Hong Kong)

^f SAARLAND UNIVERSITY   (Germany)

^g Go Vivace Inc   (United States)

^h JOHNS HOPKINS UNIVERSITY   (United States)

ⁱ MCGILL UNIVERSITY   (Canada)

Author keywords

Gaussian Mixture Models; Hidden markov models; Speech recognition

Indexed keywords

ACOUSTIC MODELING; COMMUNICATION CHANNELS (INFORMATION THEORY); GAUSSIAN DISTRIBUTION; OBJECT RECOGNITION; SPEECH RECOGNITION; TRELLIS CODES;

ACOUSTICS MODEL; COMPACT REPRESENTATION; CONVENTIONAL MODELING; GAUSSIAN MIXTURE MODEL; HIDDEN-MARKOV MODELS; MODELING APPROACH; PARAMETER SPACES; SUBSPACE GAUSSIAN MIXTURE MODELS; TRAINING DATA;

HIDDEN MARKOV MODELS;

EID: 78049409301     PISSN: 15206149     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/ICASSP.2010.5495662     Document Type: Conference Paper

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