Human behavior state profile mapping based on recalibrated speech affective space model

People typically associate health with only physical health. However, health is also interconnected to mental and emotional health. People who are emotionally healthy are in control of their behaviors and experience better quality of life. Hence, understanding human behavior is very important in ens...

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Published in:Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
Main Author: Kamaruddin N.; Wahab A.
Format: Conference paper
Language:English
Published: 2012
Online Access:https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880820876&doi=10.1109%2fEMBC.2012.6346354&partnerID=40&md5=64546b1def36b4308d1cd439b9b0ca06
id 2-s2.0-84880820876
spelling 2-s2.0-84880820876
Kamaruddin N.; Wahab A.
Human behavior state profile mapping based on recalibrated speech affective space model
2012
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS


10.1109/EMBC.2012.6346354
https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880820876&doi=10.1109%2fEMBC.2012.6346354&partnerID=40&md5=64546b1def36b4308d1cd439b9b0ca06
People typically associate health with only physical health. However, health is also interconnected to mental and emotional health. People who are emotionally healthy are in control of their behaviors and experience better quality of life. Hence, understanding human behavior is very important in ensuring the complete understanding of one's holistic health. In this paper, we attempt to map human behavior state (HBS) profiles onto recalibrated speech affective space model (rSASM). Such an approach is derived from hypotheses that: 1) Behavior is influenced by emotion, 2) Emotion can be quantified through speech, 3) Emotion is dynamic and changes over time and 4) the emotion conveyance is conditioned by culture. Empirical results illustrated that the proposed approach can complement other types of behavior analysis in such a way that it offers more explanatory components from the perspective of emotion primitives (valence and arousal). Four different driving HBS; namely: distracted, laughing, sleepy and normal are profiled onto the rSASM to visualize the correlation between HBS and emotion. This approach can be incorporated in the future behavior analysis to envisage better performance. © 2012 IEEE.

1557170X
English
Conference paper

author Kamaruddin N.; Wahab A.
spellingShingle Kamaruddin N.; Wahab A.
Human behavior state profile mapping based on recalibrated speech affective space model
author_facet Kamaruddin N.; Wahab A.
author_sort Kamaruddin N.; Wahab A.
title Human behavior state profile mapping based on recalibrated speech affective space model
title_short Human behavior state profile mapping based on recalibrated speech affective space model
title_full Human behavior state profile mapping based on recalibrated speech affective space model
title_fullStr Human behavior state profile mapping based on recalibrated speech affective space model
title_full_unstemmed Human behavior state profile mapping based on recalibrated speech affective space model
title_sort Human behavior state profile mapping based on recalibrated speech affective space model
publishDate 2012
container_title Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS
container_volume
container_issue
doi_str_mv 10.1109/EMBC.2012.6346354
url https://www.scopus.com/inward/record.uri?eid=2-s2.0-84880820876&doi=10.1109%2fEMBC.2012.6346354&partnerID=40&md5=64546b1def36b4308d1cd439b9b0ca06
description People typically associate health with only physical health. However, health is also interconnected to mental and emotional health. People who are emotionally healthy are in control of their behaviors and experience better quality of life. Hence, understanding human behavior is very important in ensuring the complete understanding of one's holistic health. In this paper, we attempt to map human behavior state (HBS) profiles onto recalibrated speech affective space model (rSASM). Such an approach is derived from hypotheses that: 1) Behavior is influenced by emotion, 2) Emotion can be quantified through speech, 3) Emotion is dynamic and changes over time and 4) the emotion conveyance is conditioned by culture. Empirical results illustrated that the proposed approach can complement other types of behavior analysis in such a way that it offers more explanatory components from the perspective of emotion primitives (valence and arousal). Four different driving HBS; namely: distracted, laughing, sleepy and normal are profiled onto the rSASM to visualize the correlation between HBS and emotion. This approach can be incorporated in the future behavior analysis to envisage better performance. © 2012 IEEE.
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issn 1557170X
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