A neural wake-sleep learning architecture for associating robotic facial emotions

—A novel wake-sleep learning architecture for processing a robot’s facial expressions is introduced. According to neuroscience evidence, associative learning of emotional responses and facial expressions occurs in the brain in the amygdala. Here we propose an architecture inspired by how the amygdala receives information from other areas of the brain to discriminate it and generate innate responses. The architecture is composed of many individual Helmholtz machines using the wake-sleep learning algorithm for performing information transformation and recognition. The Helmholtz machine is used since its re-entrant connections support both supervised and unsupervised learning. Potentially it can explain some aspects of human learning of emotional concepts and experience. In this research, a robotic head’s facial expression dataset is used. The objective of this learning architecture is to demonstrate the neural basis for the association of recognized facial expressions and linguisti...

• Type: Conference
• Year: 2008
• Where: IJCNN
• Authors: Chi-Yung Yau, Kevin Burn, Stefan Wermter
• Keywords: Artificial Intelligence, Facial Expression, IJCNN 2008, Robot’s Facial Expressions, Wake-sleep Learning