FER in Primary School Children for Affective Robot Tutors

Abstract

In the last few years, robotics has attracted much interest as a tool to support education through social interaction. Since Social- Emotional Learning (SEL) influences academic success, affective robot tutors have a great potential within education. In this article we report on our research in recognition of facial emotional expressions, aimed at improving ARTIE, an integrated environment for the development of affective robot tutors. A Full Convolutional Neural Network (FCNN) model has been trained with the Fer2013 dataset, and then validated with another dataset containing facial images of primary school children, which has been compiled during computing lab sessions. Our first prototype recognizes primary school children facial emotional expressions with 69,15% accuracy. As a future work we intend to further refine the ARTIE Emotional Component with a view to integrating the main singularities of primary school children emotional expression.