Impact of Different Feedback Mechanisms in EMG-Based Speech Recognition

This paper reports on our recent research in the feedback effects of Silent Speech. Our technology is based on surface electromyography (EMG) which captures the electrical potentials of the human articulatory muscles rather than the acoustic speech signal. While recognition results are good for loudly articulated speech and when experienced users speak silently, novice users usually achieve far worse results when speaking silently. Since there is no acoustic feedback when speaking silently, we investigate different kinds of feedback modes: no additional feedback except the natural somatosensory feedback (like the touching of the lips), visual feedback using a mirror and indirect acoustic feedback by speaking simultaneously to a previously recorded audio signal. In addition we examine recorded EMG data when the subject speaks audibly and silently in a loud environment to see if the Lombard effect can be observed in Silent Speech, too.