Multimodal Frustration Detection on Smartphones

Abstract

Detecting user's frustration on a smartphone could have a significant impact on applications such as intelligent tutoring systems or app testing systems. Our goal is to provide a multimodal frustration detection system using data exclusively retrieved from a smartphone; motion sensor readings, touch gestures and face videos recorded from the smartphone's front camera.