Tardis

Jan 24, 2019
Video

I was involved in the EU FP7 Tardis Project. TARDIS aimed to build a scenario-based serious-game simulation platform for young people (ages 18-25) at risk of exclusion to explore, practice and improve their social skills. TARDIS facilitates the interaction through virtual agents (VAs) acting as recruiters in job interviews scenarios. My contribution in this project focused on the virtual recruiter. I proposed a data-driven model allowing VAs to express different interpersonal attitudes (dominant, friendly…) which takes into account how the recruiter’s non-verbal behaviors are sequenced. The model uses a dataset of non-verbal behavior sequences obtained using sequence mining techniques, and can generate new sequences to express a chosen interpersonal attitude.

Tardis Virtual Agents Social Skills Training Social Attitudes
Avatar
Mathieu Chollet
Lecturer - Virtual Social Interactions

My research interests include interactive virtual humans and multimodal behaviour understanding through social signal processing. My application domains include social skills training, healthcare and wellbeing, and team collaboration.

Related

Publications

A Methodology for the Automatic Extraction and Generation of Non-Verbal Signals Sequences Conveying Interpersonal Attitudes

IEEE In many applications, Embodied Conversational Agents (ECAs) must be able to express various affects such as emotions or social …
Project DOI

Towards a socially adaptive virtual agent

This paper presents a socially adaptive virtual agent that can adapt its behaviour according to social constructs (e.g. attitude, …
Project DOI

Agents Conversationnels Animés pour l’entrainement social : modèle computationnel de l’expression d’attitudes sociales par des séquences de signaux non-verbaux

The Embodied Conversational Agents (ECAs) used in social training must be able to simulate all the different social situations that a …
PDF Project

An architecture for a socially adaptive virtual recruiter in job interview simulations

Project

From non-verbal signals sequence mining to bayesian networks for interpersonal attitudes expression

In this paper, we present a model and its evaluation for expressing attitudes through sequences of non-verbal signals for Embodied …
Project DOI

Expressing social attitudes in virtual agents for social coaching

The use of virtual agents in social coaching has increased rapidly in the last decade. In social coaching, the virtual agent should be …
PDF Project

Expressing social attitudes in virtual agents for social coaching

This paper presents a model of social attitudes for reasoning about the appropriate attitude to express during an interaction. It …
PDF Project

Mining a multimodal corpus for non-verbal signals sequences conveying attitudes

Interpersonal attitudes are expressed by non-verbal behaviors on a variety of different modalities. The perception of these behaviors …
PDF Project

Expressing social attitudes in virtual agents for social training games

The use of virtual agents in social coaching has increased rapidly in the last decade. In order to train the user in different …
PDF Project

Investigating Non-Verbal Behaviors Conveying Interpersonal Stances

The study of the expression of affects and their expression by Embodied Conversational Agents is complex. This is because affects are …
PDF Project

A multimodal corpus for the study of non-verbal behavior expressing interpersonal stances

PDF Project

A multimodal corpus approach to the design of virtual recruiters

This paper presents the analysis of the multimodal behavior of experienced practitioners of job interview coaching, and describes a …
Project DOI

The TARDIS framework: Intelligent virtual agents for social coaching in job interviews

The TARDIS project aims to build a scenario-based serious-game simulation platform for NEETs and job-inclusion associations that …
Project DOI