Multimodal meeting analysis by segmentation and classification of meeting events based on a higher level semantic approach

This paper encompasses the analysis of meetings for a segmentation into sub-genres. Therefore an approach on a higher semantic level has been chosen. The algorithms make use of the results of specialized recognizers like a speaker turn detector and a gesture recognizer. Basically, the goal of this investigation was to answer the question, how well meeting analysis is possible if only the results of these recognizers are available. After introducing shortly the basics of these recognizers two slightly different methods for the segmentation are presented. The results show the potential of the used methods to find the segment boundaries and to categorize the detected segments into sub-genres (also called meeting events or group actions). Based on this segmentation further analysis regarding topic detection and content extraction can be accomplished.