Multimodal Annotations and Categorization for Political Debates

The paper introduces an annotation scheme for a political debate dataset which is mainly in the form of video, and audio annotations. The annotation contains various information ranging from general linguistic to domain specific information. Some are annotated with automatic tools, and some are manually annotated. One of the goals is to use the information to predict the categories of the answers by the speaker to the disruptions. A typology of such answers is proposed and an automatic categorization system based on a multimodal parametrization is successfully performed.