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Subvocal Speech Recognition Based on EMG Signal Using Independent Component Analysis and Neural Network MLP

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4 Author(s)
Mendes, J.A.G. ; Fed. Univ. of Maranhao -Brazil, Sao Luis ; Robson, R.R. ; Labidi, S. ; Barros, A.K.

The performance of speech recognition systems is commonly degraded by either speech-related disabilities or by real-world factors such as the environmentpsilas noise level and reverberation. In this work, we propose a subvocal speech recognition system based on EMG signal for subvocal acquisition, Independent Component Analysis (ICA) for feature extraction and Neural Networks for classification. We have evaluated the systempsilas performance using a vowel phonemes database. The success rate was 93,99%.

Published in:

Image and Signal Processing, 2008. CISP '08. Congress on  (Volume:1 )

Date of Conference:

27-30 May 2008

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