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Affect Recognition from Lip Articulations

Abstract: 

Lips deliver visually active clues for speech articulation. Affective states define how humans articulate speech; hence, they also change articulation of lip motion. In this paper, we investigate effect of phonetic classes for affect recognition from lip articulations. The affect recognition problem is formalized in discrete activation, valence and dominance attributes. We use the symmetric Kullback-Leibler divergence (KLD) to rate phonetic classes with larger discrimination across different affective states. We perform experimental evaluations using the IEMOCAP database. Our results demonstrate that lip articulations over a set of discriminative phonetic classes improves the affect recognition performance, and attains 3-class recognition rates for the activation, valence and dominance (AVD) attributes as 72.16%, 46.44% and 64.92%, respectively.

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Paper Details

Authors:
Rizwan Sadiq, Engin Erzin
Submitted On:
23 March 2017 - 1:44pm
Short Link:
Type:
Poster
Event:
Presenter's Name:
Rizwan Sadiq
Paper Code:
MLSP-P1.05
Document Year:
2017
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Document Files

sadiq-erzin-icassp17.pdf

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[1] Rizwan Sadiq, Engin Erzin, "Affect Recognition from Lip Articulations", IEEE SigPort, 2017. [Online]. Available: http://sigport.org/1609. Accessed: Jul. 22, 2019.
@article{1609-17,
url = {http://sigport.org/1609},
author = {Rizwan Sadiq; Engin Erzin },
publisher = {IEEE SigPort},
title = {Affect Recognition from Lip Articulations},
year = {2017} }
TY - EJOUR
T1 - Affect Recognition from Lip Articulations
AU - Rizwan Sadiq; Engin Erzin
PY - 2017
PB - IEEE SigPort
UR - http://sigport.org/1609
ER -
Rizwan Sadiq, Engin Erzin. (2017). Affect Recognition from Lip Articulations. IEEE SigPort. http://sigport.org/1609
Rizwan Sadiq, Engin Erzin, 2017. Affect Recognition from Lip Articulations. Available at: http://sigport.org/1609.
Rizwan Sadiq, Engin Erzin. (2017). "Affect Recognition from Lip Articulations." Web.
1. Rizwan Sadiq, Engin Erzin. Affect Recognition from Lip Articulations [Internet]. IEEE SigPort; 2017. Available from : http://sigport.org/1609