• Journal of Digital Convergence
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• v.12 no.4
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• pp.157-170
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• 2014

Professional coffee shops are trying to increase customers' satisfaction and to invite more customers by providing the differentiated services. The existing researches show that the effects which the physical environment in shops has on customers' satisfaction and word of mouth intention are appealing to people's attention. In comprehensively examining the studies related to the physical environment, they can be summarized into two main perspectives, that is, the direct effect that the physical environment has on customers' satisfaction, quality perception, and other customers' responses (purchase desire, revisit intention, etc.) and the indirect effect that the physical environment has on customers' responses by means of customers' emotion or value perception. This research established 4 hypotheses by sampling 321 customers of those who have visited professional coffee shops, and empirically analyzed them. The empirical analysis carried out the structure analysis of covariance by using SPSS 17.0 statistics package and AMOS 17.0. As a result of the hypothesis qualification, the other hypotheses excluding one little hypothesis were adopted. The one refused hypothesis is that the only symbolism of the environmental elements in shops doesn't influence the customers' emotion positively (+). This is considered as a very unexpected result, and yet many customers who visit coffee shops express the symbols of professional coffee shops using the expressions such as 'bean coffee shop' or 'star coffee shop', but these expressions seem not to influence customers' mind positively in practice.

• The Journal of the Acoustical Society of Korea
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• v.34 no.3
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• pp.247-255
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• 2015

This paper presents a study on the performance of the music search based on the automatically recognized music-emotion labels. As in the other media data, such as speech, image, and video, a song can evoke certain emotions to the listeners. When people look for songs to listen, the emotions, evoked by songs, could be important points to consider. However; very little study has been done on the performance of the music-emotion labels to the music search. In this paper, we utilize the three axes of human music perception (valence, activity, tension) and the five basic emotion labels (happiness, sadness, tenderness, anger, fear) in measuring music similarity for music search. Experiments were conducted on both genre and singer datasets. The search accuracy of the proposed emotion-based music search was up to 75 % of that of the conventional feature-based music search. By combining the proposed emotion-based method with the feature-based method, we achieved up to 14 % improvement of search accuracy.

• Proceedings of the Korean Society of Broadcast Engineers Conference
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• fall
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• pp.120-123
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• 2021

디지털화와 기술의 급격한 발전으로 방송 서비스도 고품질 서비스를 보다 편리하게 이용할 수 있도록 진화하고 있다. 이러한 변화하는 방송 환경에서 비장애인 대비 소외계층의 정보 접근성을 높이기 위한 연구에 대한 필요성이 증가하고 있다. 이러한 연구의 일환으로 UHD 자막 방송 서비스를 개선하기 위한 연구인 '감성표현 자막 서비스 기술' 연구를 진행하였다. 감성표현 자막 서비스 기술은 단순한 텍스트의 전달이 아닌 이미지와 폰트 스타일을 포함한 다양한 시각적 표현을 통해 청각장애인의 방송 내용에 대한 이해도를 향상시키기 위한 기술이다. 본 논문에서는 이러한 감성표현 자막 서비스를 소개하고 해당 서비스를 가능하게 하는 관련 기술과 시스템 구현 결과에 대하여 다룬다. 지상파 UHD 방송을 대상으로 개선된 형태의 자막 서비스를 제공하기 위한 핵심 시스템인 감성자막 편집기를 개발하였다. 감성자막 편집기는 화자의 감정 정보 등을 입력, 편집하고 편집된 감성자막을 영상과 싱크를 맞추어 재생하는 기술과 감성자막을 UHD 송출시스템으로 전송하는 시스템이다.

• Journal of Korean Home Economics Education Association
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• v.17 no.1 s.35
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• pp.69-84
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• 2005

The purpose of this study was to develop and evaluate the effectiveness of an educational program, based on the family life education theory and the needs of the adolescents, for the improvement of the relationship between adolescents and their parents. Aimed to be applicable in the actual school environment, the program was practiced and successfully proved its effectiveness. Named 'Parents and I : Is It Good This Way? Over the Generation Gap', the program is composed of themes such as 'Understanding the importance of the parent-child relationship', 'Understanding parents', and 'Having friendly communication with parents', and was practiced five times, once every week, at H girls' high school located in Seoul. An evaluation was done on adolescents to see the effectiveness of the parent-child relationship improvement program: there was a meaningful distinction between the results of the pre-test and the post-test. The participants responded that they could have a chance to understand their mid-aged parents and to express their feelings and thoughts, and evaluated that the anger-control program was a training for them to express their emotions in a rational way.

• Korean Journal of Cognitive Science
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• v.35 no.1
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• pp.23-48
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• 2024

Building human-aligned artificial intelligence (AI) for social support remains challenging despite the advancement of Large Language Models. We present a novel method, the Chain of Empathy (CoE) prompting, that utilizes insights from psychotherapy to induce LLMs to reason about human emotional states. This method is inspired by various psychotherapy approaches-Cognitive-Behavioral Therapy (CBT), Dialectical Behavior Therapy (DBT), Person-Centered Therapy (PCT), and Reality Therapy (RT)-each leading to different patterns of interpreting clients' mental states. LLMs without CoE reasoning generated predominantly exploratory responses. However, when LLMs used CoE reasoning, we found a more comprehensive range of empathic responses aligned with each psychotherapy model's different reasoning patterns. For empathic expression classification, the CBT-based CoE resulted in the most balanced classification of empathic expression labels and the text generation of empathic responses. However, regarding emotion reasoning, other approaches like DBT and PCT showed higher performance in emotion reaction classification. We further conducted qualitative analysis and alignment scoring of each prompt-generated output. The findings underscore the importance of understanding the emotional context and how it affects human-AI communication. Our research contributes to understanding how psychotherapy models can be incorporated into LLMs, facilitating the development of context-aware, safe, and empathically responsive AI.

• Proceedings of the Korea Contents Association Conference
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• 2012.05a
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• pp.3-4
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• 2012

사용자 중심의 man machine interface 기술의 발전은 사용자 인터페이스 기술과 인간공학의 접목으로 인하여 많은 진전이 있으며 계속 진행되고 있다. 근래의 정보전달은 사운드와 텍스트 또는 영상을 통하여 이루어지고 있으나, 감성적인 측면에서의 정보전달에 관한 연구는 활발하지 못한 실정이다. 특히, Human Computer Interaction분야에서 음성이나 표정의 전달에 관한 감성연구는 초기단계로 이모티콘이나 플래쉬콘 등이 감정전달을 위하여 사용되고 있으나 부자연스럽고 기계적인 실정이다. 본 연구는 사용자와 상호작용에서 컴퓨터 또는 응용소프트웨어 등이 자신의 가상객체(Software Robot, Sobot)를 활용하여 인간친화적인 상호작용을 제공하기위한 기반연구로써 한글에서 감성어를 추출하여 분류하고 처리하는 기술을 개발하여 컴퓨터가 전달하고자하는 정보에 인공감정을 이입시켜 사용자들의 감성만족도를 향상시키는데 적용하고자한다.

• The Korean Journal of Coaching Psychology
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• v.6 no.1
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• pp.1-32
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• 2022

The purpose of this study is to verify the effectiveness of developing and applying a strength-based art coaching program to improve psychological and social maturity for slow learners attending elementary school. To this end, 32 slow elementary school learners living in the Seoul area were selected to form 16 experimental groups and 16 control groups. A total of 10 session of strength-based art coaching programs were conducted once a week for 60 minutes for 16 experimental groups. The main contents of the program consisted of recognizing positive psychological strengths and utilizing strengths in daily life, recognizing and empathizing with my emotions and other people's feelings, and learning and expressing specific ways of expressing my thoughts. To verify the effectiveness of the program, psychological and social maturity tests (emotional stability, social competence, communication skills, school life adaptation, interpersonal friendliness) were conducted in advance, post, 4 weeks later, and 2 weeks later. The implications of the study through the results of this study, limitations of the study, and suggestions for future research were discussed.

• Korean Security Journal
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• no.37
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• pp.269-293
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• 2013

Raising the level of quality of the security industry is an urgent matter. Since security service is provided through direct contact with customers, the security agents' expression of emotion directly influences the evaluation of the security company or their own earnings. So emotion control at customers demand is necessary above all things, and this research established what difference the service career makes in the influence that the security agent's emotional labor exerts on customer orientation, and the results of the analysis are summarized as follows. First, the security agent's emotional labor exerted negative effects on customer orientation. From this, the conclusion that the higher the security agent's emotional labor, the lower the customer orientation, was obtained. Second, the service career showed differences in the effects of the security agent's emotional labor on the customer orientation. In other words, the conclusion that the lower the security agent's service career, the greater effects the emotional labor exerts on the customer orientation, was obtained. In conclusion, in order to raise the level of customer service, systematic education to control the emotional labor of the security agents with low service career is necessary. Particularly, since the emotional labor of new employees is related to the service environment, the improvement of the service environment of the security agents is more important than anything else.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.20 no.4
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• pp.177-188
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• 2019

Emotional labor is the process of regulating feelings or emotions and expressing them in the way that fulfill job requirement. There have been many studies about characteristics or related variables of service workers' emotional labor, but are few studies comparing emotional labor between service workers and non-service workers. Therefore we are to examine the differences of emotional labor among the different types of workers. And as depression and lowered quality of life are well known negative consequences of emotional labor, we also intend to study the relationship between depression, quality of life, and emotional labor. Data were collected from 125 sales workers, and 186 cyber university full time students. And as to assure the student participants to be non-service workers, we limited the participant job as administrator, soldier or housewife. To compare differences of groups, one-way ANOVA was performed with Fisher's LSD as post hoc comparison. On overload in customer reception, service workers showed significantly higher scores, and on demand of emotional regulation/emotional dissonance/depression, both service workers and housewives showed significantly higher scores. Also analysis of multiple regression was performed, and the result showed that, emotional dissonance increased depression but decreased quality of life, while support/care increased quality of life, but decreased depression. With the result, implications and limitations of this study were discussed.

• The Transactions of the Korea Information Processing Society
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• v.13 no.6
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• pp.284-290
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• 2024

Speech emotion recognition (SER) is a technique that is used to analyze the speaker's voice patterns, including vibration, intensity, and tone, to determine their emotional state. There has been an increase in interest in artificial intelligence (AI) techniques, which are now widely used in medicine, education, industry, and the military. Nevertheless, existing researchers have attained impressive results by utilizing acted-out speech from skilled actors in a controlled environment for various scenarios. In particular, there is a mismatch between acted and spontaneous speech since acted speech includes more explicit emotional expressions than spontaneous speech. For this reason, spontaneous speech-emotion recognition remains a challenging task. This paper aims to conduct emotion recognition and improve performance using spontaneous speech data. To this end, we implement deep learning-based speech emotion recognition using the VGG (Visual Geometry Group) after converting 1-dimensional audio signals into a 2-dimensional spectrogram image. The experimental evaluations are performed on the Korean spontaneous emotional speech database from AI-Hub, consisting of 7 emotions, i.e., joy, love, anger, fear, sadness, surprise, and neutral. As a result, we achieved an average accuracy of 83.5% and 73.0% for adults and young people using a time-frequency 2-dimension spectrogram, respectively. In conclusion, our findings demonstrated that the suggested framework outperformed current state-of-the-art techniques for spontaneous speech and showed a promising performance despite the difficulty in quantifying spontaneous speech emotional expression.