A multi-views multi-learners approach towards dysarthric speech recognition using multi-nets artificial neural networks

IEEE Transactions on Neural Systems and Rehabilitation Engineering

Volumn 22, Issue 5, 2014, Pages 1053-1063

  Shahamiri, Seyed Reza ^a   Salim, Siti Salwah Binti ^a  

^a UNIVERSITY OF MALAYA   (Malaysia)

Author keywords

Dysarthria; Dysarthric speech recognition; Multi nets artificial neural networks; Multi views multi learners (MVML)

Indexed keywords

COMPLEX NETWORKS; NEURAL NETWORKS; SPEECH;

AUTOMATIC SPEECH RECOGNITION; DYSARTHRIA; LEARNER MODEL; MULTI-VIEWS; REFERENCE MODELING; SPEAKER DEPENDENTS; SPEAKER INDEPENDENTS; SPEECH RECOGNIZER;

SPEECH RECOGNITION;

ADOLESCENT; ADULT; ALGORITHM; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; AUTOMATIC SPEECH RECOGNITION; BIOLOGICAL MODEL; DYSARTHRIA; FEMALE; HUMAN; MALE; MIDDLE AGED; PSYCHOLOGY; SPEECH INTELLIGIBILITY; SPEECH PERCEPTION; YOUNG ADULT;

ADOLESCENT; ADULT; ALGORITHMS; ARTIFICIAL INTELLIGENCE; DYSARTHRIA; FEMALE; HUMANS; MALE; MIDDLE AGED; MODELS, NEUROLOGICAL; NEURAL NETWORKS (COMPUTER); SPEECH INTELLIGIBILITY; SPEECH PERCEPTION; SPEECH RECOGNITION SOFTWARE; YOUNG ADULT;

EID: 84908383294     PISSN: 15344320     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNSRE.2014.2309336     Document Type: Article

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