It has been shown that adding expressivity and emotional expressions to an agent’s communication systems would improve the interaction quality between this agent and a human user. In this paper we present a multimodal database of affect bursts, which are very short non-verbal expressions with facial, vocal, and gestural components that are highly synchronized and triggered by an identifiable event. This database contains motion capture and audio data of affect bursts representing disgust, startle and surprise recorded at three different levels of arousal each. This database is to be used for synthesis purposes in order to generate affect bursts of these emotions on a continuous arousal level scale.

A synchronous database of acoustic and 3D facial marker data was built for audio-visual laughter synthesis. Since the aim is to use this database for HMM-based modeling and synthesis, the amount of collected data from one given subject had to be maximized. The corpus contains 251 utterances of laughter from one male participant. Laughter was elicited with the help of humorous videos. The resulting database is synchronous between modalities (audio and 3D facial motion capture data). Visual 3D data is available in common formats such as BVH and C3D with head motion and facial deformation independently available. Data is segmented and audio has been annotated. Phonetic transcriptions are available in the HTK-compatible format. Principal component analysis has been conducted on visual data and has shown that a dimensionality reduction might be relevant. The corpus may be obtained under a research license upon request to authors.