• Proceeding of Spring/Autumn Annual Conference of KHA
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• 2011.04a
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• pp.247-250
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• 2011

The purpose of this study suggests the emotion of residents as indexes in Korean housing environment for providing a fundamental guideline for precise dwelling social science and indicating the view for understanding of residents in korean housing culture in korea. So this paper explores the role of residents emotion indexes in housing environment and community. For this study, survey and depth-interview methods were used for data collection. The subjects were 514 housewives living in apartments. The statistical methods for data analysis were frequency, mean, multiple linear regression and logistic regression analysis using the SPSS 18.0 program The major findings are as follows: 1)Pride of neighborhood, pride of apartment complex and sense of superiority were important factors for residental satisfaction. 2)Conspicuous image of neighbors and active contact with neighbors were import factors for their neighborship in the apartment complex. The results develop the housing environment evaluation indexes in community through the contextual understanding of space emotion society.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 1997.11a
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• pp.91-94
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• 1997

Objective of this stuey was to find the corrdlation between emotiona changes and the parameters of HRV spectrum evoked by tactile stimualtion. Twenty-one subjects were useds and five different types of materials, dry cottn, wet cotton, paper, sandpaper, and vinyl were applied to the left hand of each subject as a tactile stimulation. The results showed that HF/LF(ratio of high to low frequency amplitude calculated from power spectrum of HRV) decreased as the subject experienced the unpleasant emotion caused by wet cotton and sandpaper. On the othr hand, when the subject experienced the comfort, HF/LF increased. It was concluded that the proprsed methods can be applied to evaluate the characteristic changes in the autonomic nervous system which regulates the human emotion in the psychological aspects.

• Korean Journal of Health Psychology
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• v.15 no.3
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• pp.483-498
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• 2010

This study is to examine the effects of emotion regulation strategies in facial expressions and emotional experiences, based on the facial expressions of groups, using antecedent- and response- focused regulation. 50 female undergraduate students were instructed to use different emotion regulation strategies during the viewing of a disgust inducing film. While watching, their facial expressions and emotional experiences were measured. As a result, participants showed the highest frequency of action units related to disgust in the EG(expression group), and they reported in the following order of DG(expressive dissonance group), CG(cognitive reappraisal group), and SG(expressive suppression group). Also, the upper region of the face reflected real emotions. In this region, the frequency of action units related to disgust were lower in the CG than in the EG or DG. The results of the PANAS indicated the largest decrease of positive emotions reported in the DG, but an increase of positive emotions reported in the CG. This study suggests that cognitive reappraisal to an event is a more functional emotion regulation strategy compared to other strategies related to facial expression and emotional experience that affect emotion regulation strategies.

• Korean Journal of Child Studies
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• v.37 no.4
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• pp.117-128
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• 2016

Objective: The purpose of this study was to explore the structural relationships of child negative emotionality, mother rejective parenting, teacher-child conflict, and child emotion regulation on child aggression. Methods: The participants in this study were 3- to 5-year-old kindergarten children, their mothers, and their teachers (all of whom lived in Busan). The data were analyzed using PASW Statistics 18.0 and AMOS 21.0. For data analysis, frequency, Cronbach's alphas, Pearson's correlation coefficients, SEM were used. Results: First, mother rejective parenting had an indirect effect on child aggression through child emotion regulation. Second, teacher-child conflict had a direct effect on child aggression and had an indirect effect on child aggression through child emotion regulation. Third, child negative emotionality had an indirect effect on child aggression through mother rejective parenting and teacher-child conflict and child emotion regulation. Conclusion: These finding suggest the importance of mediating effect of mother rejective parenting, teacher-child conflict and child emotion regulation between child negative emotionality and aggression.

• Journal of Korea Society of Digital Industry and Information Management
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• v.8 no.1
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• pp.29-40
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• 2012

A challenging research issue that has been one of growing importance to those working in human-computer interaction are to endow a machine with an emotional intelligence. Thus, emotion recognition technology plays an important role in the research area of human-computer interaction, and it allows a more natural and more human-like communication between human and computer. In this paper, we propose the multimodal emotion recognition system using face and speech to improve recognition performance. The distance measurement of the face-based emotion recognition is calculated by 2D-PCA of MCS-LBP image and nearest neighbor classifier, and also the likelihood measurement is obtained by Gaussian mixture model algorithm based on pitch and mel-frequency cepstral coefficient features in speech-based emotion recognition. The individual matching scores obtained from face and speech are combined using a weighted-summation operation, and the fused-score is utilized to classify the human emotion. Through experimental results, the proposed method exhibits improved recognition accuracy of about 11.25% to 19.75% when compared to the most uni-modal approach. From these results, we confirmed that the proposed approach achieved a significant performance improvement and the proposed method was very effective.

• Science of Emotion and Sensibility
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• v.26 no.3
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• pp.83-100
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• 2023

This study determines whether the perception of the frequency of experiencing positive, negative, and surprise emotions changes according to the level of cognitive well-being. Furthermore, we determined practical means to analyze which emotions can be managed in daily life as an effective means of improving overall life satisfaction by identifying representative specific emotions that strongly predict the level of cognitive well-being. To this end, the between-subjects factorial design is adopted to measure the frequency of emotional experiences according to the level of cognitive well-being in 438 university undergraduate students. For cognitive well-being, the life satisfaction scale (SWLS) was used, and the PANAS-X scale was used to measure emotional frequency. As a result, first, the group with high cognitive well-being displays a higher frequency of positive and surprise emotional experiences and a lower frequency of negative emotional experiences than the group with low cognitive well-being. Second, the results confirm that representative emotions affecting cognitive well-being included 8 positive emotions, 7 negative emotions, and 1 surprise emotion. Among them, positive emotions include "happy" and "confident," negative emotions include "dissatisfied with self" and "disgusted with self," and surprise emotions include words such as "amazed." Therefore, we can conclude that the representative emotions are those with the greatest influence on cognitive well-being. Therefore, increasing the frequency of specific emotions (e.g., happy, confident, and surprise) and decreasing the frequency of others (e.g., dissatisfied with self and disgusted with self) could be effective in improving cognitive well-being than unconditionally examining emotions experienced in daily life.

• Journal of Oriental Neuropsychiatry
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• v.13 no.2
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• pp.21-39
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• 2002

Objectives : This study is designed to evaluate the psychological characteristics of Sasang Constitution(Origin and Nature & Emotion Group) by MBTI. Methods : 200 people were tested by QSCCII(Origin and Nature & Emotion Group) and MBTI. It is analyzed by ANOVA, Frequency, Crosstabulation, Duncan & Scheffe Post Hoc Tests. Results : 1. The number of Soyangin was 73, Soeumin was 49, Taeumin was 50, Not classified was 28 in Origin group and Soyangin was 114, Soeumin was 28, Taeumin was. 26 in Nature & Emotion group. When we evaluate QSCCII with 38 Nature & Emotion questionaires, the number of Soyangin are incresed compare to Origin Group. 2. The most three MBTI Types are Soyangin ISTJ, ISTP, ESTJ, Soeumin IJST, ISTP, INTJ, Taeumin ISTJ, ESTP, ESTJ, in Origin Group and Soyangin ISTJ, ESTJ, ISTP, Soeumin ISTJ, ISTP, INTJ, Taeumin ISTJ, ESTP, ISFP in Nature & Emotion Group. There is no significant difference between Origin and Nature & Emotion Group in ststistics. 3. Soeumin & Taeumin tended to be introverted, judging types in Origin and Nature & Emotion Group. Soeumin tended to be intuition type in Nature & Emotion Group. Conclusion : We have not significant differences on peculiarity of sasang constitution compared to MBTI between Origin and Nature & Emotion Group in ststistics.

• Korean Journal of Culture and Social Issue
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• v.27 no.4
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• pp.475-503
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• 2021

The purpose of this study is to clarify the constructs of emotion suppression and help understanding on the multidimensional nature of emotion suppression by classifying constructs for suppression according to the KMW model. Also, this study examined the gender differences of emotion suppression. For this purpose, 657 adult male and female subjects were evaluated for attitude toward emotions, and difficulty in emotional regulation, as well as depression, state anger and daily stress scale. As a result of the exploratory factor analysis on the scales related to the emotion suppression factors, the emotion suppression factors corresponding to each stage of the KMW model were found to be 'distraction against emotional information, 'difficulty in understanding and interpretation of emotions', 'emotion control beliefs', 'vulnerability on emotional expression beliefs'. Next, the study participants were classified by performing a cluster analysis based on each emotion suppression factor. As a result, four clusters were extracted and named 'emotional control belief cluster', 'emotional expression cluster', 'emotional attention failure cluster', and 'general emotional suppression cluster'. As a result of examining the average difference of male depression, depression, state anger, and daily stress for each group, significant differences were found in all dependent variables. As a result of examining whether there is a difference in the frequency of emotional suppression clusters according to gender, the frequency of emotional suppression clusters was high in men, and the ratio of emotional expression clusters was high in women. Finally, it was analyzed whether there was a gender difference in the effect of the emotional suppression cluster on psychosocial adaptation, and the implications were discussed based on the results of this study.

• Journal of the Korea Society of Computer and Information
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• v.29 no.9
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• pp.79-87
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• 2024

This study aims to improve communication for people with hearing impairments by developing artificial intelligence models that recognize and classify emotions from voice data. To achieve this, we utilized three major AI models: CNN-Transformer, HuBERT-Transformer, and Wav2Vec 2.0, to analyze users' voices in real-time and classify their emotions. To effectively extract features from voice data, we applied transformation techniques such as Mel-Frequency Cepstral Coefficient (MFCC), aiming to accurately capture the complex characteristics and subtle changes in emotions within the voice. Experimental results showed that the HuBERT-Transformer model demonstrated the highest accuracy, proving the effectiveness of combining pre-trained models and complex learning structures in the field of voice-based emotion recognition. This research presents the potential for advancements in emotion recognition technology using voice data and seeks new ways to improve communication and interaction for individuals with hearing impairments, marking its significance.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06a
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• pp.255-258
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• 2011

An application of Gammatone auditory filterbank for emotion recognition from speech is described in this paper. Gammatone filterbank is a bank of Gammatone filters which are used as a preprocessing stage before applying feature extraction methods to get the most relevant features for emotion recognition from speech. In the feature extraction step, the energy value of output signal of each filter is computed and combined with other of all filters to produce a feature vector for the learning step. A feature vector is estimated in a short time period of input speech signal to take the advantage of dependence on time domain. Finally, in the learning step, Hidden Markov Model (HMM) is used to create a model for each emotion class and recognize a particular input emotional speech. In the experiment, feature extraction based on Gammatone filterbank (GTF) shows the better outcomes in comparison with features based on Mel-Frequency Cepstral Coefficient (MFCC) which is a well-known feature extraction for speech recognition as well as emotion recognition from speech.