In this paper, we demonstrate speech recognition using electroencephalography (EEG) signals obtained using dry electrodes on a limited English vocabulary consisting of three vowels and one word using a deep learning model. We demonstrate a test accuracy of 79.07 percent on a subset vocabulary consisting of two English vowels. Our results demonstrate the feasibility of using EEG signals recorded using dry electrodes for performing the task of speech recognition.
- Pub Date:
- August 2020
- Electrical Engineering and Systems Science - Audio and Speech Processing;
- Computer Science - Machine Learning;
- Computer Science - Sound;
- Electrical Engineering and Systems Science - Signal Processing