摘要：Summary Recently electromyography (EMG) based speech signals have been used as pattern recognition of phoneme, vocal frequency estimation, browser interface, and classification of speech related problem identification. Attempts have been made to use EMG signal for sub-vocal speech pattern recognition of Hindi phonemes ▪▪▪▪ and Hindi words. That provides the command sub-vocally to control the devices. Sub-vocal EMG data were collected from more than 10 healthy subjects aged between 25 and 30 years. EMG-based sub-vocal database are acquired from four channel BIOPAC MP-30 acquisition system. Four pairs of Ag-AgCl electrodes placed in the participant neck area of skin. AR coefficients and Cepstral coefficients were computed as features of EMG-based sub-vocal signal. Furthermore, these features are classified by HMM classifier. H2M MATLAB toolbox was used to develop HMM classifier for classification of phonemes. Results were averaged on 10 subjects. An average classification accuracy of Ka is found to be 85% whereas the classification accuracy of Kha and Gha is in between 88% and 90%. The classification accuracy rate of Ga was found to be 78% which was lesser as compared to Kha and Gha.
关键词：Subvocal; EMG; Hindi phonemes; AR coefficients;
