Detection of Hidden Laughter for Human-agent Interaction

Our goal is to make a system to detect the times at which one almost laughed but he or she did not show their laughter on his/her face. We define this kind of laughter as hidden laughter. To accomplish this goal, we first tried making decision trees to detect one's amusement, the input data of...

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Published inProcedia computer science Vol. 35; pp. 1053 - 1062
Main Authors Tatsumi, Shiho, Mohammad, Yasser, Ohmoto, Yoshimasa, Nishida, Toyoaki
Format Journal Article
LanguageEnglish
Published Elsevier B.V 2014
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Abstract Our goal is to make a system to detect the times at which one almost laughed but he or she did not show their laughter on his/her face. We define this kind of laughter as hidden laughter. To accomplish this goal, we first tried making decision trees to detect one's amusement, the input data of which were physiological indices. We used 10-fold cross validation to evaluate the trees, and their accuracy was more than 70%. In addition, we investigated the effect of cultural background on the accuracy.
AbstractList Our goal is to make a system to detect the times at which one almost laughed but he or she did not show their laughter on his/her face. We define this kind of laughter as hidden laughter. To accomplish this goal, we first tried making decision trees to detect one's amusement, the input data of which were physiological indices. We used 10-fold cross validation to evaluate the trees, and their accuracy was more than 70%. In addition, we investigated the effect of cultural background on the accuracy.
Author Nishida, Toyoaki
Mohammad, Yasser
Ohmoto, Yoshimasa
Tatsumi, Shiho
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10.1037/0022-3514.54.4.592
10.1007/978-3-642-31087-4_13
10.1299/jsmermd.2009._1P1-E08_1
10.1109/ICPR.2010.764
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hidden laughter
ECG
FEMG
diaphragm
physiological index
laughter
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SubjectTerms diaphragm
ECG
FEMG
hidden laughter
laughter
physiological index
SCR
Title Detection of Hidden Laughter for Human-agent Interaction
URI https://dx.doi.org/10.1016/j.procs.2014.08.192
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