Preface for special issue on “Emotional intelligence and ambient intelligence”
J Ambient Intell Human Comput
Preface for special issue on ''Emotional intelligence and ambient intelligence''
Pau-Choo Chung 0 1 2
Bernadette Bouchon-Meunier 0 1 2
Chuan-Yu Chang 0 1 2
0 C.-Y. Chang National Yunlin University of Science and Technology , Taiwan, R.O.C
1 B. Bouchon-Meunier University Paris 6 , Paris , France
2 P.-C. Chung (&) National Cheng Kung University , Taiwan, R.O.C
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In psychology, emotion that reflects the genuine inner
feeling of a person experiencing encounters is shown to be
a major index in the evaluation of cognition, behavior, and
social skills. Emotion is also one source controlling the
learning efficiency in education, and one of essential
elements in realizing smart interaction for a computer. Thus,
emotional intelligence, which is defined as the capability to
be able to perceive, to assess and to manage emotions of
ones self or others emotion is attracting its attention in
psychology cognition, education, and machine intelligence
for achieving ambient intelligence.
Understanding ones emotion can be achieved from
several observations, including facial expression, voice
expression, and physiological signals. Emotion revealing is
affected by culture and personal characteristics; therefore,
detection/understanding human emotion is highly
challenging. On the other hand, how and why emotion affects
human mental states and reactions is still a mystery. All of
these are major issues for realizing an emotional
intelligence smart environment.
The goal of this special issue is to provide a forum for
bringing the experts from cross disciplinary to address the
emerging topic of emotional intelligence. After rigorous
reviewing and accurate revision, seven papers were
selected for publication. Tan et al. applied two bipolar
facial electromyography (EMG) channels over corrugator
supercilii and zygomaticus for differentiating the
emotional states visual stimuli in the valence arousal
dimensions. Experimental results show that corrugator EMG and
zygomaticus EMG efficiently differentiated negative and
positive emotions. Lee et al. developed a regularized
discriminant analysis (RDA)-based boosting algorithm,
and applied it on the facial emotion recognition. The
small sample size and ill-posed problems suffered from
QDA and LDA was resolved in the paper through a
regularization technique. They also used a particle swarm
optimization (PSO) algorithm to estimate optimal
parameters in RDA. Lin et al. constructed an extensible
lexicon and use semantic clues to analyze the emotions of
sentences posted on the Plurk website. A support vector
machine is applied to classify the emotions. Cerezo et al.
proposed a facial affect recognizer to sense emotions from
users facial image. Five classifiers were integrated to
identify emotions. In addition, a Kalman filtering
technique was applied to ensure the temporal consistency and
increase the robustness. Chi et al. investigates a clean
train/noisy test scenario to simulate practical conditions
with unknown noisy sources. They extracted statistics of
joint spectro-temporal modulation features from an
auditory perceptual model for the detection of the emotion
status of the speech samples which are corrupted with
white and babble noise under various SNR levels. Ana
et al. built a virtual pet by using the Ortony, Clore and
Collins (OCC) theory to implement a cognitive structure.
The methodology starts from developing a Behavior
Cognitive Task Analysis (BCTA) to elucidate the
components necessary to simulate behaviors and mental
models of virtual pets. In particular, the Fuzzy C-Mean
(FCM) is also proposed to map interaction between
elements in the emotion model. Fu et al. proposed a
TVbased information service system, ETVNetSers, to offer
family communication, social interaction, aged
entertainment, health service and home care service, for the elders.
In order to show how to sense the mental requirement of
the elders in daily living and to offer information services
dedicated to the elders, the elderly LOHAS Index (ELI) is
proposed to evaluate the happiness and wellbeing of the
elders.
Dr. Bernadette Bouchon-Meunier , University Paris 6, France (...truncated)