Syllable-based speech recognition using EMG

Lopez Larraz, Eduardo, Martinez Mozos, Oscar, Antelis, Javier M. and Minguez, Javier (2010) Syllable-based speech recognition using EMG. In: Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC), 31 Aug - 4 Sep 2010, Buenos Aires.

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This paper presents a silent-speech interface based on electromyographic (EMG) signals recorded in the facial muscles. The distinctive feature of this system is that it is based on the recognition of syllables instead of phonemes or words, which is a compromise between both approaches with advantages as (a) clear delimitation and identification inside a word, and (b) reduced set of classification groups. This system transforms the EMG signals into robust-in-time feature vectors and uses them to train a boosting classifier. Experimental results demonstrated the effectiveness of our approach in three subjects, providing a mean classification rate of almost 70% (among 30 syllables).

Keywords:electromyography, feature extraction, medical signal processing, signal classification, speech recognition
Subjects:G Mathematical and Computer Sciences > G760 Machine Learning
G Mathematical and Computer Sciences > G710 Speech and Natural Language Processing
Divisions:College of Science > School of Computer Science
ID Code:9411
Deposited On:12 May 2013 17:49

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