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2010

Mining Group Nonverbal Conversational Patterns Using Probabilistic Topic Models

8 years 6 months ago
Mining Group Nonverbal Conversational Patterns Using Probabilistic Topic Models
Abstract--The automatic discovery of group conversational behavior is a relevant problem in social computing. In this paper, we present an approach to address this problem by defining a novel group descriptor called bag of group-nonverbal-patterns (NVPs) defined on brief observations of group interaction, and by using principled probabilistic topic models to discover topics. The proposed bag of group NVPs allows fusion of individual cues and facilitates the eventual comparison of groups of varying sizes. The use of topic models helps to cluster group interactions and to quantify how different they are from each other in a formal probabilistic sense. Results of behavioral topics discovered on the Augmented Multi-Party Interaction (AMI) meeting corpus are shown to be meaningful using human annotation with multiple observers. Our method facilitates "group behavior-based" retrieval of group conversational segments without the need of any previous labeling.
Dinesh Babu Jayagopi, Daniel Gatica-Perez
Added 22 May 2011
Updated 22 May 2011
Type Journal
Year 2010
Where TMM
Authors Dinesh Babu Jayagopi, Daniel Gatica-Perez
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