The SEMAINE Database: Annotated Multimodal Records of Emotionally Coloured Conversations between a Person and a Limited Agent

Gary McKeown, Michel Valstar, Roddy Cowie, Maja Pantic, Marc Schröder

In: IEEE Transactions on Affective Computing (TAC) 99 Seiten 1-1 IEEE 7/2011.


SEMAINE has created a large audiovisual database as part of an iterative approach to building Sensitive Artificial Listener (SAL) agents that can engage a person in a sustained, emotionally coloured conversation. Data used to build the agents came from interactions between users and an 'operator' simulating a SAL agent, in different configurations: Solid SAL (designed so that operators displayed appropriate non-verbal behaviour) and Semi-automatic SAL (designed so that users' experience approximated interacting with a machine). We then recorded user interactions with the developed system, Automatic SAL, comparing the most communicatively competent version to versions with reduced nonverbal skills. High quality recording was provided by 5 high-resolution, high framerate cameras, and 4 microphones, recorded synchronously. Recordings total 150 participants, for a total of 959 conversations with individual SAL characters, lasting approximately 5 minutes each. Solid SAL recordings are transcribed and extensively annotated: 6-8 raters per clip traced five affective dimensions and 27 associated categories. Other scenarios are labelled on the same pattern, but less fully. Additional information includes FACS annotation on selected extracts, identification of laughs, nods and shakes, and measures of user engagement with the automatic system. The material is available through a web-accessible database.


Deutsches Forschungszentrum für Künstliche Intelligenz
German Research Center for Artificial Intelligence