Myoelectric signal classification for phoneme-based speech recognition

IEEE Transactions on Biomedical Engineering

Volumn 54, Issue 4, 2007, Pages 694-699

  Scheme, Erik J ^a   Hudgins, Bernard ^a   Parker, Phillip A ^a  

^a UNIVERSITY OF NEW BRUNSWICK   (Canada)

Author keywords

EMG; HMM; Multi expert systems; Myoelectric signal; Speech recognition

Indexed keywords

COMPUTER SIMULATION; ELECTROMYOGRAPHY; EXPERT SYSTEMS; HIDDEN MARKOV MODELS; MUSCLE; SIGNAL TO NOISE RATIO; SPEECH ANALYSIS; SPEECH RECOGNITION;

ARTICULATORY MUSCLES; EMG; MYOELECTRIC SIGNALS (MES); PHONEMES; SIGNAL CLASSIFICATION;

ACOUSTIC WAVES;

ACCURACY; ARTICLE; AUDITORY STIMULATION; ELECTROMYOGRAM; FACE MUSCLE; FEMALE; HUMAN; HUMAN EXPERIMENT; INFORMATION PROCESSING; MALE; MYOELECTRIC CONTROL; MYOELECTRICITY; NOISE; NORMAL HUMAN; PHONEME; PROBABILITY; SIGNAL NOISE RATIO; SPEECH DISCRIMINATION;

ALGORITHMS; ELECTROMYOGRAPHY; EXPERT SYSTEMS; FACIAL MUSCLES; HUMANS; MUSCLE CONTRACTION; PATTERN RECOGNITION, AUTOMATED; REPRODUCIBILITY OF RESULTS; SENSITIVITY AND SPECIFICITY; SPEECH; SPEECH PRODUCTION MEASUREMENT; SPEECH RECOGNITION SOFTWARE;

EID: 33947515196     PISSN: 00189294     EISSN: None     Source Type: Journal    
DOI: 10.1109/TBME.2006.889175     Document Type: Article

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