• KIISE Transactions on Computing Practices
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• v.23 no.6
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• pp.386-391
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• 2017

In this paper, we propose a system that automatically assigns user's experience-based emotion tags from wearable sensor data collected in real life. Four types of emotional tags are defined considering the user's own emotions and the information which the user sees and listens to. Based on the collected wearable sensor data from multiple sensors, we have trained a machine learning-based tagging system that combines the known auxiliary tools from the existing affective computing research and assigns emotional tags. In order to show the usefulness of this multi-modality-based emotion tagging system, quantitative and qualitative comparison with the existing single-modality-based emotion recognition approach are performed.

• The Journal of Society for e-Business Studies
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• v.17 no.1
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• pp.75-90
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• 2012

The aim of this study is to investigate the preferred website's design factors. Social computing is driving a dramatic evolution of the Web these days, and a number of users are increasing every day. But many website designers are just focusing on functional aspects of website. Also, there are few studies regarding the social computing website's emotional design. Proper designs of social computing websites could be designed through investigating the websites design factors preferred by users. Empirical study was conducted in order to investigate websites design factors preferred by users. Website design and user emotion of social computing websites were measured by the questionnaire and 254 people participated. Also, Website design and user emotion of non-social computing websites were measured by same participants, and then comparing results each other. Five design factors and eight emotion factors were derived, and only four out of design factors and three out of emotion factors were found as having significant effects on the satisfaction of social computing website. In addition, different factors in determining user satisfaction when using social computing websites and non-social computing website.

• The Journal of the Korea Contents Association
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• v.13 no.12
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• pp.184-200
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• 2013

In post-industrial society, the ability to feel and express emotion is becoming ever more important. In diverse areas of our lives such as economic, social, political and cultural activities, we are witnessing an increased application of the emotional dimension. This paper deals with the human experiences in emotional designs. Literature reviews and case analyses have been used as the main research methods. I first examine the aspects of emotional experience in designs, and then go on to analyze the components of each aspect. Emotional experience in designs has three basic aspects : (a) initially there exist user's emotional needs (b) then these emotions are delivered through design, (c) finally, emotions expressed in designs are experienced by the user. Followings are the related components for each aspect : (a) Physiological, psychological, social and cultural factors cause one to feel emotional needs. (b) Emotion is delivered either through visual symbols, experience, interaction and participation. (c) Emotion is experienced by sensing, feeling, thinking, acting and relating.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.7
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• pp.1572-1580
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• 2010

This thesis presents an emotion-based contents player platform that can change its visual and aural components as user's emotions. It analyzes the emotion as pleasant, unpleasant, aroused, and relaxed based on the physiological signals and the user's active response. Accordingly. the system reorganizes graphical and aural stimuli, such as, light, color, sound, in real-time. It can be used to develop and show the emotional contents and also be applied for the systematic analysis to find out how the components would affect the emotion. This paper describes overall the system architecture and the implementations of the sub-systems, as well as the actual contents built on top of the platform.

• Proceedings of the Korean Society for Emotion and Sensibility Conference
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• 2008.10a
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• pp.74-77
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• 2008

Online shoppers are not able to try clothing on. Therefore, the pictures of clothing on the website play a significant role when shoppers make decision on their purchase. There are generally three different ways to show clothing at online shops. The first one is showing only clothing images, and the second one is showing the pictures that have actual fitting models wearing clothing on (In this case, Model's face is mostly not shown in the picture.), and the third is showing the pictures of professional fitting models who wear goods. The shopping malls adopt each of the different ways but little is known about affect on purchasing from these three ways. The aim of this study is to figure out how the online shopper's emotional status is affected by these three ways of presenting pictures of clothing. At first, we developed a set of adjective words of human emotion to set up the evaluation criteria for user's emotional status. Those adjectives are originally from the precedent research on human emotion. To cut 99 adjectives down to a proper number for the criteria, we conducted a preliminary survey, and finally, 5 adjectives are selected as appropriate criteria for evaluating users' emotional status while they are shopping. Those five adjectives are 'possess','sensual', 'unique', 'tasteful', and 'stylish'. Then, we conducted the main survey showing 10 kinds of cloth (each cloth was consist of 3 ways). And in the page of model images, we measured the model's preference for understanding the relation with customer's emotion criteria of the product. As a result of the test there was statistically significant difference between product only images and anonymous images, but there was no significant difference between anonymous images and model images. And the preference of the model and value of the emotion criteria have large correlation except 'unique' criteria. It is expected that the result in this study will help to build new marketing strategy which satisfy customers' emotion.

• 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.

• IEMEK Journal of Embedded Systems and Applications
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• v.3 no.2
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• pp.91-101
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• 2008

For a friendly interaction between human and robot, emotional interchange has recently been more important. So many researchers who are investigating the emotion generation model tried to naturalize the robot's emotional state and to improve the usability of the model for the designer of the robot. And also the various emotion generation of the robot is needed to increase the believability of the robot. So in this paper we used the hybrid emotion generation architecture, and defined the generalized context input of emotion generation model for the designer to easily implement it to the robot. And we developed the personality and loyalty model based on the psychology for various emotion generation. Robot's personality is implemented with the emotional stability from Big-Five, and loyalty is made of familiarity generation, expression, and learning procedure which are based on the human-human social relationship such as balance theory and social exchange theory. We verify this emotion generation model by implementing it to the 'user calling and scheduling' scenario.

• Proceedings of the Korea Contents Association Conference
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• 2008.05a
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• pp.43-48
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• 2008

And this study intends to discuss especially the one using emotional filter among various information processing methods. The existing music recommendation service on the web has a weak point that it makes the user feel bored by recommending songs only with similar feeling of the same genre, because music is classified by tune, melody, atmosphere and genre before recommendation. The service using emotion filter, suggested in this study, recommends the song and lyrics appropriate to the current emotional state of the user by abstracting emotional words that could reflect the sensitivity of human and then search the words within lyrics to match in order to overcome the weak point of the existing service. This study starts where the current emotional status for the user is being input. As for the range to choose, there are the seven representatives of emotion which are, love, separation, joy, sorrow-gloom, happiness-lonesome, and anger. As the service receives input of user's emotion, it matches the emotional words appropriate for the emotion input with the lyrics, and ranks the lyrics in the order of priority, so that it recommends the song and it lyrics to the user.

• Journal of Korea Multimedia Society
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• v.20 no.10
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• pp.1646-1654
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• 2017

Pupil size variation can not be controlled intentionally by the user and includes various features such as the blinking frequency and the duration of a blink, so it is suitable for understanding the user's emotional state. In addition, an ocular feature based emotion classification method should be studied for virtual and augmented reality, which is expected to be applied to various fields. In this paper, we propose a novel emotion classification based on CNN with pupil size variation signals which include not only various ocular feature information but also time information. As a result, compared to previous studies using the same database, the proposed method showed improved results of 5.99% and 12.98% respectively from arousal and valence emotion classification.

• KIISE Transactions on Computing Practices
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• v.21 no.2
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• pp.160-165
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• 2015

Traditional speech emotion recognition techniques recognize emotions using a general training model based on the voices of various people. These techniques can not consider personalized speech character exactly. Therefore, the recognized results are very different to each person. This paper proposes an adaptive speech emotion recognition framework made from user's' immediate feedback data using a prompted labeling technique for building a personal adaptive recognition model and applying it to each user in a mobile device environment. The proposed framework can recognize emotions from the building of a personalized recognition model. The proposed framework was evaluated to be better than the traditional research techniques from three comparative experiment. The proposed framework can be applied to healthcare, emotion monitoring and personalized service.