Abstract

In this paper we present a novel approach for a surface electromyographic speech recognition system based on sub-word units. Rather than using full word models as integrated in our previous work we propose here smaller sub-word units as prerequisites for large vocabulary speech recognition. This allows the recognition of words not seen in the training set based on seen sub-word units. Therefore we report on experiments with syllables and phonemes as sub-word units. We also developed a new feature extraction method that gains significant improvement for words and sub-word units. Index Terms: silent speech, non-audible speech recognition, electromyography, sub-word unit comparison

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