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Modeling Collaborative Multimodal Behavior in Group Dialogues: The MULTISIMO Corpus

We present a multimodal corpus that has been recently developed within the MULTISIMO project and targets the investigation and modeling of collaborative aspects of multimodal behavior in groups that perform simple tasks. The corpus consists of a set of human-human interactions recorded in multiple modalities. In each interactive session two participants collaborate with each other to solve a quiz while assisted by a facilitator. The corpus has been transcribed and annotated with information related to verbal and non-verbal signals. A set of additional annotation and processing tasks are currently in progress. The corpus includes survey materials, i.e. personality tests and experience assessment questionnaires filled in by all participants. This dataset addresses multiparty collaborative interactions and aims at providing tools for measuring collaboration and task success based on the integration of the related multimodal information and the personality traits of the participants, but also at modeling the multimodal strategies that members of a group employ to discuss and collaborate with each other. The corpus is designed for public release.