• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.2
• /
• pp.197-203
• /
• 2005

In this paper, we propose an emotion recognition using facial Images to effectively design human interface. Facial database consists of six basic human emotions including happiness, sadness, anger, surprise, fear and dislike which have been known as common emotions regardless of nation and culture. Emotion recognition for the facial images is performed after applying the discrete wavelet. Here, the feature vectors are extracted from the PCA and LDA. Experimental results show that human emotions such as happiness, sadness, and anger has better performance than surprise, fear and dislike. Expecially, Japanese shows lower performance for the dislike emotion. Generally, the recognition rates for Korean have higher values than Japanese cases.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2001.12a
• /
• pp.203-207
• /
• 2001

In this Paper, we propose the neural network based emotion recognition method for intelligently recognizing the human's emotion using CCD color image. To do this, we first acquire the color image from the CCD camera, and then propose the method for recognizing the expression to be represented the structural correlation of man's feature Points(eyebrows, eye, nose, mouse) It is central technology that the Process of extract, separate and recognize correct data in the image. for representation is expressed by structural corelation of human's feature Points In the Proposed method, human's emotion is divided into four emotion (surprise, anger, happiness, sadness). Had separated complexion area using color-difference of color space by method that have separated background and human's face toughly to change such as external illumination in this paper. For this, we propose an algorithm to extract four feature Points from the face image acquired by the color CCD camera and find normalization face picture and some feature vectors from those. And then we apply back-prapagation algorithm to the secondary feature vector. Finally, we show the Practical application possibility of the proposed method.

• International Journal of Fuzzy Logic and Intelligent Systems
• /
• v.5 no.1
• /
• pp.1-6
• /
• 2005

In this paper, we propose an emotion recognition method using the facial images and speech signals. Six basic emotions including happiness, sadness, anger, surprise, fear and dislike are investigated. Facia] expression recognition is performed by using the multi-resolution analysis based on the discrete wavelet. Here, we obtain the feature vectors through the ICA(Independent Component Analysis). On the other hand, the emotion recognition from the speech signal method has a structure of performing the recognition algorithm independently for each wavelet subband and the final recognition is obtained from the multi-decision making scheme. After merging the facial and speech emotion recognition results, we obtained better performance than previous ones.

• Journal of information and communication convergence engineering
• /
• v.19 no.3
• /
• pp.148-154
• /
• 2021

With the advent of context-aware computing, many attempts were made to understand emotions. Among these various attempts, Speech Emotion Recognition (SER) is a method of recognizing the speaker's emotions through speech information. The SER is successful in selecting distinctive 'features' and 'classifying' them in an appropriate way. In this paper, the performances of SER using neural network models (e.g., fully connected network (FCN), convolutional neural network (CNN)) with Mel-Frequency Cepstral Coefficients (MFCC) are examined in terms of the accuracy and distribution of emotion recognition. For Ryerson Audio-Visual Database of Emotional Speech and Song (RAVDESS) dataset, by tuning model parameters, a two-dimensional Convolutional Neural Network (2D-CNN) model with MFCC showed the best performance with an average accuracy of 88.54% for 5 emotions, anger, happiness, calm, fear, and sadness, of men and women. In addition, by examining the distribution of emotion recognition accuracies for neural network models, the 2D-CNN with MFCC can expect an overall accuracy of 75% or more.

• Journal of Distribution Science
• /
• v.14 no.7
• /
• pp.63-70
• /
• 2016

Purpose - The purpose of this study was to examine the variations in emotions during vacation and to explore if such variations depend on psychological distance perceived by vacationers. We proposed that there are changes in affect balance during the course of vacation as well as the mental construal of psychological distance. Research Design, Data, and Methodology - Repeated measures ANOVA was used to examine the variation in emotion and psychological distance of 66 holiday makers who were traveling to different destination for vacation. Data were collected in 2 months with the help of a travel agency. Results - We find that there are variations in emotions during the vacation at different points in time as well as perceived psychological distance. Also we find some evidence that suggests emotional happiness does depend on perceived mental distance to some extent. Conclusion - Our study replicates the findings of previous studies in a novel way and illustrates the robustness of the nature of emotions during vacation and indicates certain time points where the happiness of vacationers can be enhanced. Perceived psychological distance do have an effect on how happy an individual feels during the vacation.

• The Journal of the Korea Contents Association
• /
• v.12 no.4
• /
• pp.304-314
• /
• 2012

The purpose of this study was to examine relationship among life meaning, optimism and happiness in elderly women participants of physical activity. Data are from elderly women in more than 60 years old who participate in sports activity as part of leisure activity while actually living in Seoul of South Korea. Total of 211, Sample are allowed to be responded to questionnaire contents with self-administration method by utilizing convenience sampling method out of non-probability sampling. To process the data, this study conducted exploratory/confirmatory factor analysis, correlation analysis, reliability analysis and structure model analysis with SPSS 11.5 and AMOS 6.0 programs. The presence of meaning, which forms meaning of life, are indicated to have statistically significant positive influence upon optimism. And optimism are indicated to have statistically significant positive influence upon positive emotion, which forms happiness. optimism in elderly adults of participating in physical activity has negative influence upon negative emotion.

• Journal of Digital Convergence
• /
• v.15 no.6
• /
• pp.197-206
• /
• 2017

The purpose of this study is to verify the effect of positive psychology-based literacy therapy program on elementary school students' happiness by constructing a literature therapy program based on positive psychology. In order to evaluate the effectiveness of the program, the experiment group and the control group were subjected to the pre - test. The same test as that carried out in the test was conducted. The pre - and post - scores of experimental group and control group were compared and analyzed by independent sample t-test. The results of this study were as follows. First, literature therapy programs based on positive psychology were found to be effective in improving elementary school students' happiness (t = 10.175, p <.001). Second, the effects of positive psychology - based literacy therapy programs on self - esteem, optimism, friendship, and family environment were found to affect all four factors (t = 5.720, p <.001). Therefore, the children tend to equate themselves with the person in the book, so that the short and concise sentence of the poem can convey emotion and emotion to the child.

• Journal of Convergence for Information Technology
• /
• v.8 no.4
• /
• pp.99-108
• /
• 2018

This study regards the savoring, emotion and happiness of 232 equestrians who participated in leisure sports horse riding. First, exploratory factor analysis and confirmatory factor analysis were conducted to extract the main variables and to verify the validity of the study. Second, correlation analysis was performed to find out the correlation between major variables. Third, path analysis was performed to derive the final result of this study. In addition, we conducted a reliability analysis of major measurement tools to determine internal consistency(Conbach's ${\alpha}$) utilizing IBM SPSS 21.0 and IBM AMOS 21.0. The results show that past recall had a statistically significant negative impact on negative emotions and future expectations had a negative impact on positive emotions. Also, future expectations showed a statistically significant effect on euphoria and positive emotions had positive effects on happiness.

• 한국노년학
• /
• v.29 no.3
• /
• pp.1141-1158
• /
• 2009

This study was conducted to explore the determinants of happiness for Korean Old People. A total of 105 Korean old people responded to open-ended questions about their happiness. From the content analysis of those reponses were happiness-related 70 items derived. Then 200 old people rated themselves on the list of those items. Factor analysis of those data ended up with 33 items of 8 factors, which were ①Family relationship, ②Religion, ③Financial ability, ④Health, ⑤Work/Job, ⑥ Psychological stability, ⑦Leisure, ⑧Public welfare. This Happiness Scale for the Korean old people, Subjective wellbeing Scale, Emotion experience Scale, and Self-esteem Scale were also administered to the identical 200 Korean old people. Results indicated that the construct validity of this new Happiness Scale for Korean old people was obtained. Finally, the implications and limitations of the present study and suggestions for further studies were discussed.

• Speech Sciences
• /
• v.15 no.1
• /
• pp.63-72
• /
• 2008

Various acoustic features were extracted and analyzed to estimate the inter- and intra-speaker variability of emotional speech. Tokens of vowel /a/ from sentences spoken with different modes of emotion (sadness, neutral, happiness, fear and anger) were analyzed. All of the acoustic features (fundamental frequency, spectral slope, HNR, H1-A1 and formant frequency) indicated greater contribution to inter- than intra-speaker variability across all emotions. Each acoustic feature of speech signal showed a different degree of contribution to speaker discrimination in different emotional modes. Sadness and neutral indicated greater speaker discrimination than other emotional modes (happiness, fear, anger in descending order of F-ratio). In other words, the speaker specificity was better represented in sadness and neutral than in happiness, fear and anger with any of the acoustic features.