Please use this identifier to cite or link to this item: http://hdl.handle.net/1959.3/68924

Title

Gabor neural network based facial expression recognition for assistive speech expression

Author(s)

Theng, Lau Bee

Abstract

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.

Publication type

Conference paper

Research centre

Swinburne University of Technology. Sarawak Campus. School of Computing and Design

Source

Lecture notes in computer science: proceedings of the 15th International Conference on Advances in Neuro-Information Processing (ICONIP 2008), Auckland, New Zealand, 25-28 November 2008, Vol. 5507, pp. 591-598

Publication year

2009

Keyword(s)

CPC;  Facial expressions;  Face recognition;  Software;  Speech

Publisher

Springer

ISSN

0302-9743 (series ISSN)

ISBN

9783642030390, 3642030394

Publisher URL

http://dx.doi.org/10.1007/978-3-642-03040-6_72

Copyright

Copyright © Springer-Verlag Berlin Heidelberg 2009.

Peer reviewed