• Science of Emotion and Sensibility
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• v.21 no.4
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• pp.77-90
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• 2018

Behavioral studies of emotion recognition in autism spectrum disorders (ASD) have yielded mixed results. Most of the studies focused on emotion recognition abilities with regard to ASD using stimuli with unisensory modality, making it difficult to determine difficulties in real life emotion perception in ASD. Herein, we review the recent behavioral and cognitive neuroscience studies on emotion recognition functions in ASD, including both unisensory and multisensory emotional information, to elucidate the possible difficulties in emotion recognition in ASD. In our study, we discovered that people with ASD have problems in the process of integrating emotional information during emotion recognition tasks. The following four points are discussed: (1) The restrictions of previous studies, (2) deficits in emotion recognition in ASD especially in recognizing multisensory information, (3) possible compensation mechanisms for emotion recognition in ASD, and (4) the possible roles of attention and language functions in emotion recognition in ASD. The compensatory mechanisms proposed herein for ASD with regard to emotion recognition abilities could contribute to a therapeutic approach for improving emotion recognition functions in ASD.

• Fashion & Textile Research Journal
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• v.7 no.2
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• pp.162-168
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• 2005

The pictures of design details, such as collar type, sleeve type, skirt type, and skirt length, and color tone were evaluated by 377 persons in terms of sensibility and emotion. The data were analyzed by SPSS using ANOVA and Factor analysis to find out the most effective types of details on consumer's sensibility and emotion, and the methods were introduced. The most effective type is skirt length on sensibility and emotion of women's dress. The second type is different according to sensibility and emotion. Sensibility and emotion were composed of three concept: contemporary, mature and character. Sleeve type is second determinant to contemporary concept, and color tone is to mature concept, collar type is to character concept. 41 each details of design were positioned into 3D-concept space to connect each detail type and fashion concept of women's dress.

• Science of Emotion and Sensibility
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• v.8 no.1
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• pp.1-7
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• 2005

This paper reports several emotion detecting methods based on various attributes of human voice. These methods have been developed at our Engineering Systems Laboratory. It is noted that, in all of the proposed methods, only prosodic information in voice is used for emotion recognition and semantic information in voice is not used. Different types of neural networks(NNs) are used for detection depending on the type of voice parameters. Earlier approaches separately used linear prediction coefficients(LPCs) and time series data of pitch but they were combined in later studies. The proposed methods are explained first and then evaluation experiments of individual methods and their performances in emotion detection are presented and compared.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.113-115
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• 1999

인터넷에서 제공하는 각종 서비스 및 다양한 소프트웨어들은 점차 사용자를 고려하여 개발되고 있는 추세이나 아직은 미약하다. 사용자를 고려한다는 것은 사용자가 소프트웨어를 사용하거나 서비스를 받으면서 공감을 느끼도록 하여 사용 효과를 높이고, 생활의 일부분이 되어 가고 있는 컴퓨터 시스템을 사람과 친하게 만들려는 것이다. 이를 위해서는 사용자와의 상호작용이 중요시된다. 본 연구에서는 사람과 비슷한 가상의 캐릭터를 이용하며, 이 캐릭터가 사용자와 상호 작용을 통하여 emotion을 갖게 하는데 중점을 두었다. 즉, 캐릭터가 가질 수 있는 emotion structure를 정의하고 사용자와의 상호작용을 바탕으로 캐릭터의 emotion을 생성한다. 이를 위한 시스템은 사용자가 에이전트에게 task를 요청하여 서비스를 받을 때까지 일어날 수 있는 여러 상호작용에 대하여 캐릭터의 emotion을 생성하여 사용자에게 simulation하게 된다. 이러한 감정의 교류를 통하여 사용자는 캐릭터에게 친근감을 갖게 되며 캐릭터의 emotion에 대하여 공감할 수 있고 응용프로그램의 신뢰성을 높이는 효과를 가져온다.

• 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.

• Science of Emotion and Sensibility
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• v.5 no.1
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• pp.61-70
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• 2002

The purpose of this study was to develop 'Emotion Rating Scale induced by Odors'and to identify the structure of odor emotion induced by odors. At first 37 adjectives that describe odor to develop a rating scale were selected. Subjects were to rate odor emotion on a 7-point bipolar scale. 304 subjects participated and were as a group instructed to rate odor emotion. 53 out of 304 subjects were retested to test for reliability of the scale two weeks after under the same condition and finally 25 adjectives were then selected based on high test-retest reliability and factor loading, high contributing to one factor. 24 subjects each in 10s, 20s, 30s & 40s were to rate odor emotion induced by 5 different odors on the scale developed. The structure of odor emotion consisted of 'Esthetics', 'Intensity', 'Romance', 'Nature'and 'Character'. The structure of odor emotion by age appeared quite similar but that by different odors was little bit different.

• Journal of the Korean Society for Library and Information Science
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• v.32 no.4
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• pp.105-115
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• 1998

In this paper, we propose a document clustering and retrieval tool which allows users to manage their emotion based document access. This system name is ECRAS(Emotion based Clustering and Retrieval Agent System). Our system extract S emotion feature which like HAPPY, SAD, ANGRY, FEAR, DISGUST from various document. And, our system have retrieve documents for user query base on emotion feature.

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

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2011.11a
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• pp.56-58
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• 2011

• Journal of the Korea Safety Management & Science
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• v.17 no.3
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• pp.247-263
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• 2015

This study seeks to identify effects derived from emotional labor in the distribution industry, and draw ways to systematically manage the employees by exploring effects of the emotion work on performance. For the purpose, literature reviews and empirical experiments were conducted to find out effects of emotional labor and false face acting on emotion work and organizational performance and effects of social support and job autonomy on the relationship between emotion work and organizational performance. To verify the hypothesis, we conducted a hierarchical regression analysis and structural equation model analysis using SPSS 20 and AMOS19. The result of the verification in this study is as follows: First, effects of emotional labor on burnout was found to be statistically significant, second, as for the path-coefficient for "emotional labor ${\rightarrow}$ emotion work" and "emotional labor ${\rightarrow}$ job satisfaction" was not statistically significant, while the path-coefficient for "emotional labor ${\rightarrow}$ service level" was found to be statistically significant. Third, effects of emotion work on job satisfaction was found statistically significant, fourth, emotion work on the service level was found statistically significant, fifth, effects of false face acting on emotion work was found statistically significant, sixth, effects of false face acting on burnout was statistically significant, seventh, moderating were found statistically significant and lastly, moderating effects of the relationship between emotion work from job autonomy and organization performance was not verified in job satisfaction, while emotion work, job autonomy, and interaction variable in service level were statistically significant.