• Journal of Korea Game Society
• /
• v.16 no.1
• /
• pp.23-32
• /
• 2016

A recent emotion research has attracted attention as an element to enhance the interaction with the user to play the game. Emotion expressed in the previous game was using a simple structure. However, increasing the user's needs of emotions that have been used in the game is necessary to structure the emotions caused. In this paper, it was utilized for the character of emotion in the game rules of the proposed emotion based on the principle of biological feelings. And it was classified a game component that affects the emotions and character provides a structure for recognizing the emotion from the game. This paper provides a structural framework to be considered in order to analyze emotions used in existing game to the role of emotion, to express emotion in the game.

• Journal of IKEEE
• /
• v.24 no.4
• /
• pp.998-1003
• /
• 2020

In this paper, an emotion training method using emotional adaptation is proposed to improve the performance of the existing emotion recognition system. For emotion adaptation, an emotion speech model was created from a speech model without emotion using a small number of training emotion voices and emotion adaptation methods. This method showed superior performance even when using a smaller number of emotional voices than the existing method. Since it is not easy to obtain enough emotional voices for training, it is very practical to use a small number of emotional voices in real situations. In the experimental results using a Korean database containing four emotions, the proposed method using emotional adaptation showed better performance than the existing method.

• Proceedings of the Korean Institute of Intelligent Systems Conference
• /
• 2008.04a
• /
• pp.54-55
• /
• 2008

본 논문에서는 인간형 로봇의 태스크 실행 중 자율 감정 생성을 위하여 Three-layered hybrid architecture에 기반한 감정 반응 시스템을 제안한다. Three-layered hybrid architecture는 Deliberative layer, Reactive layer Hardware abstraction layer의 3단계의 계층으로 되어 있으며, 모바일 로봇의 자율 동작을 위해서 개발되었다. 본 연구에서는 저자가 개발중인 안드로이드 EveR-2의 감정 시스템에 적용하여 로봇의 태스크 동작 중에 외부의 자극들로부터 자신의 감정을 생성하고, 생성된 감정과 태스크를 조합하여 자신의 행동을 변화시키며 인간과 상호작용하는 로봇 감정 시스템을 구현하였다.

• Journal of the Korea Society of Computer and Information
• /
• v.18 no.9
• /
• pp.131-138
• /
• 2013

In this paper, I propose and evaluate the method that classifies emotional type of characters with their emotional words. Emotional types are classified as three types such as positive, negative and neutral. They are selected by classification of emotional words that characters speak. I propose the method to extract emotional words based on WordNet, and to represent as emotional vector. WordNet is thesaurus of network structure connected by hypernym, hyponym, synonym, antonym, and so on. Emotion word is extracted by calculating its emotional distance to each emotional category. The number of emotional category is 30. Therefore, emotional vector has 30 levels. When all emotional vectors of some character are accumulated, her/his emotion of a movie can be represented as a emotional vector. Also, thirty emotional categories can be classified as three elements of positive, negative, and neutral. As a result, emotion of some character can be represented by values of three elements. The proposed method was evaluated for 12 characters of four movies. Result of evaluation showed the accuracy of 75%.

• Journal of Internet Computing and Services
• /
• v.12 no.6
• /
• pp.83-94
• /
• 2011

Main researching issue in affective computing is to give a machine the ability to recognize the emotion of a person and to react it properly. Efforts in that direction have mainly focused on facial and oral cues to get emotions. Postures have been recently considered as well. This paper aims to discriminate emotions posture by identifying and measuring the saliency of posture features that play a role in affective expression. To do so, affective postures from human subjects are first collected using a motion capture system, then emotional features in posture are described with spatial ones. Through standard statistical techniques, we verified that there is a statistically significant correlation between the emotion intended by the acting subjects, and the emotion perceived by the observers. Discriminant Analysis are used to build affective posture predictive models and to measure the saliency of the proposed set of posture features in discriminating between 6 basic emotional states. The evaluation of proposed features and models are performed using a correlation between actor-observer's postures set. Quantitative experimental results show that proposed set of features discriminates well between emotions, and also that built predictive models perform well.

• Journal of Software Assessment and Valuation
• /
• v.16 no.1
• /
• pp.1-11
• /
• 2020

The March 29, 2016, amendment to the Civil Procedure Act introduced changes to the appraisal procedures, including new obligations for appraisers, changes in the modes of appraiser testimony, and questioning of appraisers through video conferencing, with all seemingly aimed at procedurally addressing the issues with appraisal in the context of court proceedings. The changes introduced by the amendment also affect the appraisal procedures for copyrights. In light of the above, this article examines how the amendment to the Civil Procedure Act affects the appraisal procedures for copyrights. Specific issues covered by this paper include: appointment of additional appraisers, prohibition of delegated appraisal, operation of the multiple appraisal system, disclosure of participating experts, proximity of the appraiser system, and congruence of areas of expertise.

• Proceedings of the Acoustical Society of Korea Conference
• /
• 1998.08a
• /
• pp.350-355
• /
• 1998

감정을 표현하는 음성 합성 시스템을 구현하기 위해서는 감정음성에 대한 분석이 필요하다. 본 논문에선,s 평상, 화남, 기쁨, 슬픔의 네 가지 감정에 대한 음성 데이터에 대해 음절 세그먼트, 라벨링을 행한 감정 음성 데이터베이스를 구축하였고, 감정표현이 음성에 영향을 미치는 요인에대하여, 운율, 음운적인 요소로 나누어 분석하였다. 또한 기본 주파수, 에너지, 음절지속시간에 대한 분석과 감정 음성의기본 주파수, 에너지, 음절지속시간, 스펙트럼 포락의 인지 정도를 측정하기 위하여 평상 음성에 감정 음성의 운율 요소를 적용하는 음성을 합성하여 ABX 방법으로 평가하였다. 그 결과, 기본 주파수의변화가 73.3%, 음절지속시간은 43.3% 로 올바른 감정으로 인지되었으며, 특히 슬픈 감정에서 음절지속시간은 76.6%가 올바르게 감정을 나타내는 것으로 인지되었다.

• Journal of The Korean Association For Science Education
• /
• v.36 no.2
• /
• pp.231-251
• /
• 2016

The goal of the study was to examine pre-service teachers' emotional experiences, especially during student teaching. The following questions guided this study. First, during student teaching, what are the characteristics of emotional experiences of pre-service science teachers? Second, what are used as the emotional rules and strategies by student teacher? In this study, we tracked nine pre-service science teachers over a four-week period of the student teaching. The data sources were lesson observations, interviews, emotional journals, and video-recorded classroom lessons. Results showed that student teachers experienced various 25 different types of emotions which were reported as the primary emotions of Koreans. The main subjects for interaction for positive emotions were students. For negative emotions, students, teachers and student teachers themselves all resulted in such negative emotional experiences. When the student teachers experienced negative emotions, they followed the emotional rule that their emotions should not be expressed in front of the students. Because of this, they tried various strategies for controlling emotions, such as 'understanding students', 'finding the positive side', 'seeing good students', 'ignoring', 'holding back', 'evading', and 'giving up'. Finally, suggestions for teacher education were discussed.

• 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.

• Korean Journal of Cognitive Science
• /
• v.19 no.4
• /
• pp.499-517
• /
• 2008

In this paper, we propose an effective emotion feature extraction method for Korean and evaluate their availability in sentiment classification. Korean emotion features are expanded from several representative emotion words and they play an important role in building in an effective sentiment classification system. Firstly, synonym information of English word thesaurus is used to extract effective emotion features and then the extracted English emotion features are translated into Korean. To evaluate the extracted Korean emotion features, we represent each document using the extracted features and classify it using SVM(Support Vector Machine). In experimental results, the sentiment classification system using the extracted Korean emotion features obtained more improved performance(14.1%) than the system using content-words based features which have generally used in common text classification systems.