• Science of Emotion and Sensibility
• /
• v.11 no.4
• /
• pp.541-552
• /
• 2008

We cannot express emotions correctly with only speech because it is hard to estimate the kind, size, amount of emotions. Hamlet who is a protagonist in 'Hamlet' of Shakespeare has emotions which cannot be expressed within only speech because he is in various dramatic situations. So we supposed an artificial emotion, instead of expressing emotion with speech, expressing and visualizing current emotions with color and location. And we visualized emotions of characters in 'Hamlet' with the artificial emotion. We designed the artificial emotion to four steps considering peculiarities of emotion. First, the artificial emotion analyzes inputted emotional stimulus as relationship between causes and effects and analyzes its kinds and amounts. Second, we suppose Emotion Graph Unit to express generating, maintaining, decaying of analyzed one emotional stimuli which is outputted by first step, according to characteristic. Third, using Emotion Graph Unit, we suppose Emotion Graph that expresses continual same emotional stimulus. And we make Emotion Graph at each emotions, managing generation and decay of emotion individually. Last, we suppose Emotion Field can express current combined value of Emotion Graph according to co-relation of various emotions, and visualize current emotion by a color and a location in Emotion Field. We adjusted the artificial emotion to the play 'Hamlet' to test and visualize changes of emotion of Hamlet and his mother, Gertrude.

• Journal of Integrative Natural Science
• /
• v.7 no.1
• /
• pp.50-56
• /
• 2014

To explore effects on each the emotional awareness, emotional expression, emotional empathy, and emotional regulation, of the sub-factors of the child's emotional intelligence, to mural preference, emotion cultivation, and community connection, the hierarchical multiple regression analyses are performed(as in Table 1, 2, and 3). As the results, we found the following facts. Children's mural preference, emotion cultivation, and community connection were expressed by the following equations in order, respectively. Mural Preference = $.170{\times}$[Emotional Awareness](t=2.118, $p=.036^*$) - $.025{\times}$[Emotional Expression](t=-.275, p=.783) + $.088{\times}$[Emotional Empathy](t=.938, p=.350) + $.139{\times}$[Emotional Regulation] (t=1.529, p=.128). Mural Emotion Cultivation = $-.021{\times}$[Emotional Awareness](t=-.294, p=.769) - $.205{\times}$[Emotional Expression](t=-2.573, $p=.011^*$) + $.265{\times}$[Emotional Empathy](t=3.156, $p=.002^*$) + $.192{\times}$[Emotional Regulation](t=2.361, $p=.019^*$). Mural Community Connection = $-.001{\times}$[Emotional Awareness](t=-.007, p=.995) - $.132{\times}$[Emotional Expression](t=-1.478, p=.141) + $.172{\times}$[Emotional Empathy](t=1.732, $p=.027^*$) + $.098{\times}$[Emotional Regulation](t=1.072, p=.285).

• Science of Emotion and Sensibility
• /
• v.18 no.4
• /
• pp.47-58
• /
• 2015

Due to recent interest in user experience and its significance, much research surrounding this theme is now being conducted. If user experience is defined as the emotions and satisfaction the user feels while using the product, how much of such experience will contribute to the overall satisfaction of using the product? In this research, user experience during usage of a product and the satisfaction acquired by it were investigated. The same experiment was conducted in South Korea and the United States of America in order to get more generalized experimental results. Amongst the six representative user emotions expressed while using a product, 'Satisfaction in Usability', 'Discomfort or Displeasure', and 'Excellence' correlated the most. The above three factors were found to be of the most influence concerning satisfaction of the product. The significance of this finding is that aside from focusing on the attractiveness of the product's exteriors and design, one should be concerned on the ease of usage and effectiveness as well as usability of the product, all of which contribute to how efficiently a consumer will utilize the product.

• International Journal of Computer Science & Network Security
• /
• v.23 no.8
• /
• pp.40-48
• /
• 2023

Speech Emotions recognition has become the active research theme in speech processing and in applications based on human-machine interaction. In this work, our system is a two-stage approach, namely feature extraction and classification engine. Firstly, two sets of feature are investigated which are: the first one is extracting only 13 Mel-frequency Cepstral Coefficient (MFCC) from emotional speech samples and the second one is applying features fusions between the three features: Zero Crossing Rate (ZCR), Teager Energy Operator (TEO), and Harmonic to Noise Rate (HNR) and MFCC features. Secondly, we use two types of classification techniques which are: the Support Vector Machines (SVM) and the k-Nearest Neighbor (k-NN) to show the performance between them. Besides that, we investigate the importance of the recent advances in machine learning including the deep kernel learning. A large set of experiments are conducted on Surrey Audio-Visual Expressed Emotion (SAVEE) dataset for seven emotions. The results of our experiments showed given good accuracy compared with the previous studies.

• Science of Emotion and Sensibility
• /
• v.17 no.1
• /
• pp.53-62
• /
• 2014

Despite the huge potential of the practical application of emotion recognition technologies, the enhancement of the technologies still remains a challenge mainly due to the difficulty of recognizing emotion. Although not perfect, human emotions can be recognized through human images and sounds. Emotion recognition technologies have been researched by extensive studies that include image-based recognition studies, sound-based studies, and both image and sound-based studies. Studies on emotion recognition through facial expression detection are especially effective as emotions are primarily expressed in human face. However, differences in user environment and their familiarity with the technologies may cause significant disparities and errors. In order to enhance the accuracy of real-time emotion recognition, it is crucial to note a mechanism of understanding and analyzing users' personality traits that contribute to the improvement of emotion recognition. This study focuses on analyzing users' personality traits and its application in the emotion recognition system to reduce errors in emotion recognition through facial expression detection and improve the accuracy of the results. In particular, the study offers a practical solution to users with subtle facial expressions or low degree of emotion expression by providing an enhanced emotion recognition function.

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2004.10a
• /
• pp.232-233
• /
• 2004

• Proceedings of the Korea Society of Design Studies Conference
• /
• 2005.10a
• /
• pp.52-53
• /
• 2005

• Science of Emotion and Sensibility
• /
• v.15 no.1
• /
• pp.105-120
• /
• 2012

This study aimed to develop a Korean emotion vocabulary list that functions as an important tool in understanding human feelings. In doing so, the focus was on the careful extraction of most widely used feeling words, as well as categorization into groups of emotion(s) in relation to its meaning when used in real life. A total of 12 professionals (including Korean major graduate students) partook in the study. Using the Korean 'word frequency list' developed by Yonsei University and through various sorting processes, the study condensed the original 64,666 emotion words into a finalized 504 words. In the next step, a total of 80 social work students evaluated and classified each word for its meaning and into any of the following categories that seem most appropriate for inclusion: 'happiness', 'sadness', 'fear', 'anger', 'disgust', 'surprise', 'interest', 'boredom', 'pain', 'neutral', and 'other'. Findings showed that, of the 504 feeling words, 426 words expressed a single emotion, whereas 72 words reflected two emotions (i.e., same word indicating two distinct emotions), and 6 words showing three emotions. Of the 426 words that represent a single emotion, 'sadness' was predominant, followed by 'anger' and 'happiness'. Amongst 72 words that showed two emotions were mostly a combination of 'anger' and 'disgust', followed by 'sadness' and 'fear', and 'happiness' and 'interest'. The significance of the study is on the development of a most adaptive list of Korean feeling words that can be meticulously combined with other emotion signals such as facial expression in optimizing emotion recognition research, particularly in the Human-Computer Interface (HCI) area. The identification of feeling words that connote more than one emotion is also noteworthy.

• Journal of the Korean Society of Costume
• /
• v.57 no.3 s.112
• /
• pp.23-36
• /
• 2007

It is important that ubiquitous technology changes paradigm of thought, not simple definition in the 21st digital era. Characteristics of ubiquitous computing are pervasive, disappearing, invisible, calm through environment. As IT Technology develops, designers, computer scientists, chemists, performance artists cooperate in order to find out the best way to make desirable digital clothing in the future, with the merit of each part. Digital clothing defines clothes of new generation equipped computer, digital installations. Digital clothing design demands intercept of electromagnetic waves, light-weight and esthetic appearance, for it is attached high-technology equipment near body. The purpose of this study is to analyze design features of digital clothing according to ubiquitous characteristics. The methods of this study are documentary research of previous study and case study. In the theoretical study, ubiquitous characteristics are function-intensive by convergence, interactivity, embedded mobility and human & emotion-oriented attributes. Based on ubiquitous characteristics, digital clothing design classified function-intensive design by convergence, design for Interactivity and multi-sensible & emotion-oriented design, because embedded mobility is a basic element of ubiquitous environment. The early days digital clothing design is function-intensive design, and have esthetic appearances and design for interactivity increasingly. Recently digital clothing design is expressed multi-sensible and emotion-oriented design.

• Journal of dental hygiene science
• /
• v.17 no.3
• /
• pp.209-217
• /
• 2017

This study investigated the relationships between experiencing verbal violence and the emotional responses and coping behaviors of dental hygienists who worked in Jeonju between February 24 and March 18, 2017 to prepare strategies for managing verbal violence and establish a healthy working environment for dental hygienists. The following findings were obtained in this study. The dental hygienists primarily experienced verbal violence from patients and guardians (1.67 points). The most common verbal violence type was, "Someone treated me impolitely." The most common emotional response to verbal violence was "anger" (3.52 points). The coping style of most dental hygienists was problem-focused coping (3.28 points), followed by emotion-focused coping (2.75 points). Most hygienists with the problem-focused coping style stated that they resolve the problem through dialogue (3.51 points), while most hygienists with the emotion-focused coping style responded that they just ignore the situation (3.78 points). The relationship between experiencing verbal violence and the emotional responses and coping behaviors of dental hygienists showed a statistically significant positive correlation (p<0.05) with emotional responses and problem- and emotion-focused coping associated with experiencing verbal violence from dentists, patients, and guardians. These findings confirm the need to reduce verbal violence, control emotional responses after exposure to verbal violence, and use more problem-focused coping measures. Dental hygienists must develop interpersonal skills and communication techniques and promote professionalism in their workplace to protect themselves from verbal violence at work.