Booth Id:
BMED013T
Category:
Biomedical and Health Sciences
Year:
2021
Finalist Names:
Karimli, Banuchichak (School: High School #11)
Mammadzade, Murad (School: High School #11)
Abstract:
This work presents a speech synthesizing interface based on electromyographic (EMG) signals recorded in the facial muscles. The distinctive feature of this system is that it is based on the recognition of buccal muscle activity and provides more sustainable connection and clear vocalization of the signals. This system transforms the EMG signals into robust-in-time feature vectors and uses them to train a boosting classifier. Experimental results demonstrated the effectiveness of our approach in three subjects, providing a mean classification rate of almost 70%.