Facial Emotion Recognition in Presence of Speech using a Default ARTMAP Classifier

Sheir Afgen Zaheer, Jong-Hwan Kim

Abstract

This paper proposes a scheme for facial emotion recognition in the presence of speech, i.e. the interacting subjects are also speaking. We propose the usage of default ARTMAP, a variant of fuzzy ARTMAP, as a classifier for facial emotions using feature vectors derived from facial animation parameters (FAP). The proposed scheme is tested on Interactive Emotional Dyadic Motion Capture (IEMOCAP) database. The results show the effectiveness of the approach as a standalone facial emotion classifier as well as its relatively superior performance on IEMOCAP in comparison to the existing similar approaches.

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Paper Citation


in Harvard Style

Zaheer S. and Kim J. (2017). Facial Emotion Recognition in Presence of Speech using a Default ARTMAP Classifier.In Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: SCT, ISBN 978-989-758-274-5, pages 436-442. DOI: 10.5220/0006572204360442


in Bibtex Style

@conference{sct17,
author={Sheir Afgen Zaheer and Jong-Hwan Kim},
title={Facial Emotion Recognition in Presence of Speech using a Default ARTMAP Classifier},
booktitle={Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: SCT,},
year={2017},
pages={436-442},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0006572204360442},
isbn={978-989-758-274-5},
}


in EndNote Style

TY - CONF

JO - Proceedings of the 9th International Joint Conference on Computational Intelligence - Volume 1: SCT,
TI - Facial Emotion Recognition in Presence of Speech using a Default ARTMAP Classifier
SN - 978-989-758-274-5
AU - Zaheer S.
AU - Kim J.
PY - 2017
SP - 436
EP - 442
DO - 10.5220/0006572204360442