Multimodal analysis of laughter for an interactive system

In this paper, we focus on the development of new methods to detect and analyze laughter, in order to enhance human-computer interactions. First, the general architecture of such a laughter-enabled application is presented. Then, we propose the use of two new modalities, namely body movements and respiration, to enrich the audiovisual laughter detection and classification phase. These additional signals are acquired using easily constructed affordable sensors. Features to characterize laughter from body movements are proposed, as well as a method to detect laughter from a measure of thoracic circumference.