Speech Recognition using EEG signals recorded using dry electrodes
This work addresses speech recognition for individuals with communication impairments, but it is incremental due to the limited vocabulary and specific setup.
The paper tackled speech recognition using EEG signals from dry electrodes on a limited English vocabulary, achieving a test accuracy of 79.07% on a subset of two vowels.
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.