This research focuses on utilizing the biometrics recognition to trigger the speech expresser. Our selected biometric is facial expression. Though CPC have no verbal language ability, they have facial expression ability that can be interpreted to relate to their voice speech needs. However facial expression of a CPC may not be exactly identical at all times. Furthermore CPC are unique and require special speech profiles. After a thorough research in face recognition and artificial intelligence domain, neural network coupled with Gabor feature extraction is found to outperform others. A Neural Network with Gabor filters is built to train the facial expression classifiers. This research has proven successful to help CPC to express their voice speech through software with 98% successful facial recognition rate. © 2009 Springer Berlin Heidelberg.
CITATION STYLE
Theng, L. B. (2009). Gabor neural network based facial expression recognition for assistive speech expression. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 5507 LNCS, pp. 591–598). https://doi.org/10.1007/978-3-642-03040-6_72
Mendeley helps you to discover research relevant for your work.