A Methodology for the Automatic Extraction and Generation of Non-Verbal Signals Sequences Conveying Interpersonal Attitudes - Archive ouverte HAL Accéder directement au contenu
Article Dans Une Revue IEEE Transactions on Affective Computing Année : 2017

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

Résumé

—Depending on their application, Embodied Conversational Agents (ECAs) must be able to express various affects or social constructs such as emotions or social attitudes. Non-verbal signals, such as smiles or gestures, contribute to the expression of attitudes. Social attitudes affect the whole behavior of a person: as Scherer puts it, they are " characteristic of an affective style that colors the entire interaction " [1]. Moreover, recent findings have demonstrated that non-verbal signals are not interpretated in isolation but along with surrounding signals: for instance, a smile followed by a gaze aversion and a head aversion may signal embarassment rather than amusement [2]. Non-verbal behavior planning models designed to allow ECAs to express attitudes should thus consider complete sequences of non-verbal signals and not only signals independently of one another. However, existing models do not take this into account, or in a limited manner. The contribution of this paper is a methodology for the automatic extraction of sequences of non-verbal signals characteristic of a social phenomenon from a multimodal corpus, and a non-verbal behavior planning model that takes into account sequences of non-verbal signals rather than signals independently. This methodology is applied to design a virtual recruiter capable of expressing social attitudes, which is then evaluated in and out of an interaction context.
Fichier principal
Vignette du fichier
tac_v4.pdf (3.51 Mo) Télécharger le fichier
Origine : Fichiers produits par l'(les) auteur(s)
Loading...

Dates et versions

hal-01793271 , version 1 (18-05-2018)

Identifiants

Citer

Mathieu Chollet, Magalie Ochs, Catherine Pelachaud. A Methodology for the Automatic Extraction and Generation of Non-Verbal Signals Sequences Conveying Interpersonal Attitudes. IEEE Transactions on Affective Computing, 2017, XX, pp.1 - 1. ⟨10.1109/TAFFC.2017.2753777⟩. ⟨hal-01793271⟩
139 Consultations
225 Téléchargements

Altmetric

Partager

Gmail Facebook X LinkedIn More