Artificial neural networks as speech recognisers for dysarthric speech: Identifying the best-performing set of MFCC parameters and studying a speaker-independent approach

Advanced Engineering Informatics

Volumn 28, Issue 1, 2014, Pages 102-110

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

^a UNIVERSITY OF MALAYA   (Malaysia)

Author keywords

Artificial neural network; Automatic speech recognition; Dysarthria; Mel frequency cepstral coefficients

Indexed keywords

DISABLED PERSONS; LOUDSPEAKERS; NEURAL NETWORKS; SPEECH; SPEECH COMMUNICATION;

ACOUSTIC FEATURES; AUTOMATIC SPEECH RECOGNITION; DYSARTHRIA; EVALUATION SUBJECT; MEL FREQUENCY CEPSTRAL CO-EFFICIENT; MEL-FREQUENCY CEPSTRAL COEFFICIENTS; SPEAKER DEPENDENTS; SPEAKER INDEPENDENTS;

SPEECH RECOGNITION;

EID: 84893724279     PISSN: 14740346     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.aei.2014.01.001     Document Type: Article

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