Analysis of Invariant Meta-features for Learning and Understanding Disable People´s Emotional Behavior Related to Their Health Conditions: A Case Study

"There are million individuals with disabilities with traumatic emotional experiences due to their health issues leading frustration and depression, where a major factor for it is their emotional behavior". Emotion is a topic that has received much attention during the last few years, both in the context of speech synthesis, image understanding as well in automatic speech recognition, interactive dialogues systems and wearable computing. There are few promising studies on the emotional behavior of people with disabilities. These studies are partial due to the lack Information technology and engineering (ITE) techniques that make available a deeper and large scale non-invasive analysis and evaluation of the disabled people emotional behavior in order to provide tools and support for helping them to overcome social and health barriers. A quantitative and qualitative study of emotional invariant meta-features to support the development of emotionally rich man-machine interfaces (interactive dialogue systems and intelligent avatars) for people with disabilities is the subject of this paper