• KIPS Transactions on Software and Data Engineering
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• v.3 no.10
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• pp.451-456
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• 2014

The correlations between electroencephalographic (EEG) spectral power and emotional responses during affective sound clip listening are important parameters. Hemispheric asymmetry in prefrontal activation have been proposed in two decades ago, as measured by power value, is related to reactivity to affectively pleasure audio stimuli. In this study, we designed an emotional audio stimulus experiment in order to verify frontal EEG asymmetry by analyzing Event-related Spectral Perturbation (ERSP) results. Thirty healthy college male students volunteered the stimulus experiment with the standard IADS(International Affective Digital Sounds) clips. These affective sound clips are classified in three emotion states, high pleasure-high arousal (happy), middle pleasure-low arousal (neutral) and low pleasure-high arousal (fear). The analysis of the data was performed in both theta (4-8Hz) and alpha (8-13Hz) bands. ERSP maps in the alpha band revealed that there are the stronger power responses of high pleasure (happy) in the right frontal lobe, while the stronger power responses of middle-low pleasure (neutral and fear) in the left frontal lobe. Moreover, ERSP maps in the theta band revealed that there are the stronger power responses of high arousal (fear and happy) in the left pre-frontal lobe, while the stronger responses of low arousal (neutral) in the right pre-frontal lobe. However, the high pleasure emotions (happy) can elicit greater relative right EEG activity, while the low and middle pleasure emotions (fear and neutral) can elicit the greater relative left EEG activity. Additionally, the most differences of theta band have been found out in the medial frontal lobe, which is proved as the frontal midline theta. And there are the strongest responses of happy sounds in the alpha band around the whole frontal regions. These results are well suited for emotion recognition, and provide the evidences that theta and alpha powers may have the more important role in the emotion processing than previously believed.

• Journal of the Korea Convergence Society
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• v.10 no.1
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• pp.245-256
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• 2019

The study is aimed at examining the influence of empathy and pro-social behavior on school life happiness of multicultural and Korean adolescents through sports activities. The results of the analysis of total 461 adolescents participating in sports activities and not participating in sports activities are as follows. Adolescents participating in sports activities have higher levels of empathy, pro-social behavior and school life happiness than those who do not participate. And the more experience involved in sports activities, the higher the level of empathy, the level of pro-social behavior and the level of school life happiness. There is a significant correlation between empathy and pro-social behavior and school life happiness. Empathy and pro-social behavior factors affecting school life happiness are statistically influencing factors such as "relationship formation", "communication", "cooperation", "assistance", "emotional expression", and "comfort". The results of this study suggest the importance of dealing with empathy and pro-social behavior through sports activities in the school life happiness of multicultural families and Korean adolescents.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.25 no.3
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• pp.101-118
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• 2014

Given the context of rapid developing ubiquitous computing environment, it is imperative for users to search and use images based on affective meanings. However, it has been difficult to index affective meanings of image since emotions of image are substantially subjective and highly abstract. In addition, utilizing low level features of image for indexing affective meanings of image has been limited for high level concepts of image. To facilitate the access points of affective meanings of image, this study aims to utilize user-provided responses of images. For a data set, emotional words are collected and cleaned from twenty participants with a set of fifteen images, three images for each of basic emotions, love, sad, fear, anger, and happy. A total of 399 unique emotion words are revealed and 1,093 times appeared in this data set. Through co-word analysis and network analysis of emotional words from users' responses, this study demonstrates expanded word sets for five basic emotions. The expanded word sets are characterized with adjective expression and action/behavior expression.

• Science of Emotion and Sensibility
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• v.20 no.2
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• pp.161-170
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• 2017

Emotion affects many parts of human life such as learning ability, behavior and judgment. It is important to understand human nature. Emotion can only be inferred from facial expressions or gestures, what it actually is. In particular, emotion is difficult to classify not only because individuals feel differently about emotion but also because visually induced emotion does not sustain during whole testing period. To solve the problem, we acquired bio-signals and extracted features from those signals, which offer objective information about emotion stimulus. The emotion pattern classifier was composed of unsupervised learning algorithm with hidden nodes and feature vectors. Restricted Boltzmann machine (RBM) based on probability estimation was used in the unsupervised learning and maps emotion features to transformed dimensions. The emotion was characterized by non-linear classifiers with hidden nodes of a multi layer neural network, named deep belief network (DBN). The accuracy of DBN (about 94 %) was better than that of back-propagation neural network (about 40 %). The DBN showed good performance as the emotion pattern classifier.

• Journal of the Institute of Convergence Signal Processing
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• v.3 no.3
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• pp.21-26
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• 2002

This paper presents the new approach of identifying human emotional states such as anger, happiness, normal, sadness, or surprise. This is accomplished by using discrete duration continuous hidden Markov models(DDCHMM). For this, the emotional feature parameters are first defined from input speech signals. In this study, we used prosodic parameters such as pitch signals, energy, and their each derivative, which were then trained by HMM for recognition. Speaker adapted emotional models based on maximum a posteriori(MAP) estimation were also considered for speaker adaptation. As results, the simulation performance showed that the recognition rates of vocal emotion gradually increased with an increase of adaptation sample number.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.247-255
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• 2015

This paper presents a study on the performance of the music search based on the automatically recognized music-emotion labels. As in the other media data, such as speech, image, and video, a song can evoke certain emotions to the listeners. When people look for songs to listen, the emotions, evoked by songs, could be important points to consider. However; very little study has been done on the performance of the music-emotion labels to the music search. In this paper, we utilize the three axes of human music perception (valence, activity, tension) and the five basic emotion labels (happiness, sadness, tenderness, anger, fear) in measuring music similarity for music search. Experiments were conducted on both genre and singer datasets. The search accuracy of the proposed emotion-based music search was up to 75 % of that of the conventional feature-based music search. By combining the proposed emotion-based method with the feature-based method, we achieved up to 14 % improvement of search accuracy.

• Journal of Korea Entertainment Industry Association
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• v.13 no.6
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• pp.211-220
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• 2019

It helps to wisely abstain from errors of the a priori subjective emotions related to human emotions, and orders emotions to make rational choices. These emotional happiness of human and moral sensitivities work directly or indirectly in rational choice of rational thought and reason. Abraham would have been troubled by the divine mandate to sacrifice a son who was only one, and a son who had been healed. Was his reason reasonable at this time? In rational reason, it can be said that the act of dedicating his son is an appropriate act, but is it possible in the human mind? Aristoteles also called human virtue virtue in good for human beings. Because happiness is also a mental activity, we have to know a certain degree about the mind. This ψυχή(psyche, spirit) spirit is an irrational element that is invisible but an intervention in rational principles. Also C. G. Jung states that all human beings have four dynamic psychological functions that are not visible, and that the mind is driven by these four functional dimensions. This means that the elements of S, Sensing, N, Intuition, T, Thinking, and Feeling are combined. David Hume also emphasized the principle of empathy, asserting that morality can not be derived from reason, and Max Ferdinand Scheler, before grasping the visual characteristics of a person, has already captured the whole feeling of the person, And that the value given to this feeling is the value, and that the function of emotion that is elevated to the perceived object by grasping the value through this process and the value is always preceded by the reason. Emmanuel Levinas states that emotional emotions of love are ahead of reason and that emotions precede human reasoning and rationality is the inability of emotional control that we need rational thought and rational and wise action as reason of control and temperance. As part of human emotional education, in the 7th curriculum, Bloom's cognitive, perceptive, and behavioral domain, which is a person with integrated thinking, is trying to be a moral practitioner. It focuses on how to act according to the direction of emotions for virtuous acts and how to develop emotions for emotions on behalf of vicious acts. We can design the possibility and direction of cultivating human emotions and emotional happiness and happy sensitivities by the principle of strengthening virtue and the principle of elimination of ill feeling.

• Journal of the Korean Institute of Intelligent Systems
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• v.19 no.1
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• pp.1-5
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• 2009

This paper suggests to apply mirror-reflected method based 2D emotion recognition database to 3D application. Also, it makes facial expression of fuzzy modeling using probability of emotion. Suggested facial expression function applies fuzzy theory to 3 basic movement for facial expressions. This method applies 3D application to feature vector for emotion recognition from 2D application using mirror-reflected multi-image. Thus, we can have model based on fuzzy nonlinear facial expression of a 2D model for a real model. We use average values about probability of 6 basic expressions such as happy, sad, disgust, angry, surprise and fear. Furthermore, dynimic facial expressions are made via fuzzy modelling. This paper compares and analyzes feature vectors of real model with 3D human-like avatar.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.24 no.8
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• pp.1064-1070
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• 2020

In Korea, video-based news broadcasters are primarily classified into terrestrial broadcasters, general programming cable broadcasters and YouTube broadcasters. Recently, news broadcasters get subjective while targeting the desired specific audience. This violates normative expectations of impartiality and neutrality on journalism from its audience. This phenomenon may have a negative impact on audience perceptions of issues. This study examined whether broadcast news reporting conveys emotions and if so, how news broadcasters differ according to emotion type. Emotion types were classified into neutrality, happiness, sadness and anger using a convolutional neural network which is a class of deep neural networks. Results showed that news anchors or reporters tend to express their emotions during TV broadcasts regardless of broadcast systems. This study provides the first quantative investigation of emotions in broadcasting news. In addition, this study is the first deep learning-based approach to emotion analysis of broadcasting news.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.25 no.11
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• pp.1538-1544
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• 2021

This study aims to analyze through empirical experiments for the effects of a 360 degree's VR travel contents on stress in the era of COVID-19, as stress has emerged as social problems due to restrictions on freedom of movement. For the empirical experiment, the hypothesis (Happiness level or Depression level or Arousal level will affect the level of stress after watching VR travel contents) was established. As a result, the depression level was adopted while the others were rejected. In order to relieve stress, it is necessary to be careful not to feel depressed, and it was found that even if we can't travel freely, we can reduce stress somewhat with VR travel contents in the untact era. In other words, the emotional state after watching VR travel contents has changed positively. It is hoped that the results of this study will be of some help to the tourism industry and VR production industry, which have been contracted.