Addressing Subject-dependency for Affective Signal Processing - Modeling Subjects’ Idiosyncracies

François Courtemanche, Emma Campbell, Pierre-Majorique Léger, Franco Lepore

2015

Abstract

Most works on Affective Signal Processing (ASP) focus on user-dependent emotion recognition models which are personalized to a specific subject. As these types of approach have good accuracy rates, they cannot easily be reused with other subjects for industrial or research purposes. On the other hand, the reported accuracy rates of user-independent models are substantially lower. This performance decrease is mostly due to the greater variance in the physiological training data set drawn from multiple users. In this paper, we propose an approach to address this problem and enhance the performance of user-independent models by explicitly modeling subjects’ idiosyncrasies. As a first exemplification, we describe how personality traits can be used to improve the accuracy of user-independent emotion recognition models. We also present the experiment that will be carried on to validate the proposed approach.

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Paper Citation


in Harvard Style

Courtemanche F., Campbell E., Léger P. and Lepore F. (2015). Addressing Subject-dependency for Affective Signal Processing - Modeling Subjects’ Idiosyncracies . In Proceedings of the 2nd International Conference on Physiological Computing Systems - Volume 1: PhyCS, ISBN 978-989-758-085-7, pages 72-77. DOI: 10.5220/0005330700720077


in Bibtex Style

@conference{phycs15,
author={François Courtemanche and Emma Campbell and Pierre-Majorique Léger and Franco Lepore},
title={Addressing Subject-dependency for Affective Signal Processing - Modeling Subjects’ Idiosyncracies},
booktitle={Proceedings of the 2nd International Conference on Physiological Computing Systems - Volume 1: PhyCS,},
year={2015},
pages={72-77},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005330700720077},
isbn={978-989-758-085-7},
}


in EndNote Style

TY - CONF
JO - Proceedings of the 2nd International Conference on Physiological Computing Systems - Volume 1: PhyCS,
TI - Addressing Subject-dependency for Affective Signal Processing - Modeling Subjects’ Idiosyncracies
SN - 978-989-758-085-7
AU - Courtemanche F.
AU - Campbell E.
AU - Léger P.
AU - Lepore F.
PY - 2015
SP - 72
EP - 77
DO - 10.5220/0005330700720077