GNetIc --- Using Bayesian Decision Networks for Iconic Gesture Generation

Authors:
Kirsten Bergmann;Stefan Kopp
Affiliations:
Sociable Agents Group, CITEC, Bielefeld University, Bielefeld, Germany D-33615;Sociable Agents Group, CITEC, Bielefeld University, Bielefeld, Germany D-33615
Venue:
IVA '09 Proceedings of the 9th International Conference on Intelligent Virtual Agents
Year:
2009

Citing 8
Cited 10

Speaking with hands: creating animated conversational characters from recordings of human performance

ACM SIGGRAPH 2004 Papers
Coordination and context-dependence in the generation of embodied conversation

INLG '00 Proceedings of the first international conference on Natural language generation - Volume 14
Influence Diagrams

Decision Analysis
A decision network framework for the behavioral animation of virtual humans

SCA '07 Proceedings of the 2007 ACM SIGGRAPH/Eurographics symposium on Computer animation
Gesture modeling and animation based on a probabilistic re-creation of speaker style

ACM Transactions on Graphics (TOG)
Increasing the expressiveness of virtual agents: autonomous generation of speech and gesture for spatial description tasks

Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
Presenting in style by virtual humans

COST 2102'07 Proceedings of the 2007 COST action 2102 international conference on Verbal and nonverbal communication behaviours
Implementing expressive gesture synthesis for embodied conversational agents

GW'05 Proceedings of the 6th international conference on Gesture in Human-Computer Interaction and Simulation

Modelling and evaluation of lexical and syntactic alignment with a priming-based microplanner

Empirical methods in natural language generation
Individualized gesturing outperforms average gesturing: evaluating gesture production in virtual humans

IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Generating culture-specific gestures for virtual agent dialogs

IVA'10 Proceedings of the 10th international conference on Intelligent virtual agents
Nonverbal action selection for explanations using an enhanced behavior net

IVA'11 Proceedings of the 10th international conference on Intelligent virtual agents
Systematicity and idiosyncrasy in iconic gesture use: empirical analysis and computational modeling

GW'09 Proceedings of the 8th international conference on Gesture in Embodied Communication and Human-Computer Interaction
Regulating dialogue with gestures: towards an empirically grounded simulation with conversational agents

SIGDIAL '11 Proceedings of the SIGDIAL 2011 Conference
Collection and analysis of multimodal interaction in direction-giving dialogues: towards an automatic gesture selection mechanism for metaverse avatars

AEGS'11 Proceedings of the 2011 international conference on Agents for Educational Games and Simulations
A second chance to make a first impression? how appearance and nonverbal behavior affect perceived warmth and competence of virtual agents over time

IVA'12 Proceedings of the 12th international conference on Intelligent Virtual Agents
How do iconic gestures convey visuo-spatial information? bringing together empirical, theoretical, and simulation studies

GW'11 Proceedings of the 9th international conference on Gesture and Sign Language in Human-Computer Interaction and Embodied Communication
Cultural diversity for virtual characters (extended abstract)

IJCAI'13 Proceedings of the Twenty-Third international joint conference on Artificial Intelligence

Quantified Score

Hi-index	0.00

Visualization

Abstract

Expressing spatial information with iconic gestures is abundant in human communication and requires to transform a referent representation into resembling gestural form. This task is challenging as the mapping is determined by the visuo-spatial features of the referent, the overall discourse context as well as concomitant speech, and its outcome varies considerably across different speakers. We present a framework, GNetIc, that combines data-driven with model-based techniques to model the generation of iconic gestures with Bayesian decision networks. Drawing on extensive empirical data, we discuss how this method allows for simulating speaker-specific vs. speaker-independent gesture production. Modeling results from a prototype implementation are presented and evaluated.