PASCAL - Pattern Analysis, Statistical Modelling and Computational Learning

Discovering Group Nonverbal Conversational Patterns with Topics
Dinesh Babu Jayagopi and Daniel Gatica-Perez
In: Proc. Int. Conf. on Multimodal Interfaces (ICMI-MLMI), 02-06 Nov 2009, Cambridge, USA.


This paper addresses the problem of discovering conversational group dynamics from nonverbal cues extracted from thin-slices of interaction. We first propose and analyze a novel thin-slice interaction descriptor - a bag of group nonverbal patterns - which robustly captures the turn-taking behavior of the members of a group while integrating its leader’s position. We then rely on probabilistic topic modeling of the interaction descriptors which, in a fully unsupervised way, is able to discover group interaction patterns that resemble prototypical leadership styles proposed in social psychology. Our method, validated on the Augmented Multi-Party Interaction (AMI) meeting corpus, facilitates the retrieval of group conversational segments where semantically meaningful group behaviours emerge.

PDF - PASCAL Members only - Requires Adobe Acrobat Reader or other PDF viewer.
EPrint Type:Conference or Workshop Item (Paper)
Project Keyword:Project Keyword UNSPECIFIED
Subjects:Multimodal Integration
ID Code:6856
Deposited By:Daniel Gatica-Perez
Deposited On:08 April 2010