Evaluation of Resonance in Staff Selection through Multimedia Contents

system
Example of scenario during the interview.

 

Authors:

Vitoantonio BevilacquaAngelo Antonio SalatinoCarlo Di LeoDario D’AmbruosoMarco SumaDonato BaroneGiacomo TattoliDomenico CampagnaFabio StroppaMichele Pantaleo

Abstract:

In this paper we present the results of an experimental Italian research project finalized to support the classification process of the two behavioural status (resonance and dissonance) of a candidate applying for a job position. The proposed framework is based on an innovative system designed and implemented to extract and process the non-verbal expressions like facial, gestural and prosodic of the subject, acquired during the whole job interview session. In principle, we created our own database, containing multimedia data extracted, by different software modules, from video, audio and 3D sensor streams and then used SVM classifiers that perform in terms of accuracy 72%, 79% and 63% respectively for facial, vocal and gestural features. ANN classifiers have also been used, obtaining comparable results. Finally, we combined all the three domains and then reported the results of this last classification test proving that the experimental proposed work seems to perform in a very encouraging way.

Link to the article: http://link.springer.com/chapter/10.1007/978-3-319-09339-0_19

More information about the article/book: Intelligent Computing MethodologiesLecture Notes in Computer Science Volume 8589, 2014, pp 185-198

Export Citation:

@incollection{
year={2014},
isbn={978-3-319-09338-3},
booktitle={Intelligent Computing Methodologies},
volume={8589},
series={Lecture Notes in Computer Science},
editor={Huang, De-Shuang and Jo, Kang-Hyun and Wang, Ling},
doi={10.1007/978-3-319-09339-0_19},
title={Evaluation of Resonance in Staff Selection through Multimedia Contents},
url={http://dx.doi.org/10.1007/978-3-319-09339-0_19},
publisher={Springer International Publishing},
keywords={Emotional Speech Classification; Facial Expression Recognition; Gestural Expression Recognition; SVM; ANN; Resonance; Dissonance; Emotion Recognition},
author={Bevilacqua, Vitoantonio and Salatino, AngeloAntonio and Di Leo, Carlo and D’Ambruoso, Dario and Suma, Marco and Barone, Donato and Tattoli, Giacomo and Campagna, Domenico and Stroppa, Fabio and Pantaleo, Michele},
pages={185-198},
language={English}
}