Signal acquisition and processing techniques for sEMG based silent speech recognition

Abstract

sEMG based silent speech recognition systems seek to bypass the limitations of acoustic speech recognition by measuring and interpreting muscle activity of the facial and neck musculature involved in speech production. However, this speech recognition modality introduces unique challenges of its own. This paper describes signal acquisition and processing strategies that we have employed to address these challenges during our development of a silent speech recognition system.