• Title/Summary/Keyword: Emotional Robot

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Ethical Use of Web-based Welfare Technology for Caring Elderly People Who Live Alone in Korea: A Case Study

  • Soyun Choi;Kyungsook Kim;Chayapol Kamyod;Cheong Ghil Kim
    • Journal of Web Engineering
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    • v.21 no.4
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    • pp.1239-1264
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    • 2022
  • This study examined ethical ways to use welfare technology in a situation where the demand for non-face-to-face welfare services using Cloud based healthcare systems had increased rapidly in caring for elderly people who live alone. Through focus group interviews with social workers related to the care of elderly people who live alone, in-depth interviews were conducted on the current situation, problems, ethical issues, and development directions arising in the implementation of welfare technology. The main areas of interest were focused on improving safety in caring them using IoT technology and enhancing emotional support in preventing lonely deaths using companion robot and AI speaker. Issues such as the need for individualization, client-centeredness, privacy, self-determination, competence, informed consent, right to know, convenience, and advocacy were identified as important ethical considerations related to use of welfare technology. The research results suggested that various stakeholders should participate in the development of ethical indicators and welfare technology for the ethical use of welfare technology.

A Study on Human-Robot Interaction Trends Using BERTopic (BERTopic을 활용한 인간-로봇 상호작용 동향 연구)

  • Jeonghun Kim;Kee-Young Kwahk
    • Journal of Intelligence and Information Systems
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    • v.29 no.3
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    • pp.185-209
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    • 2023
  • With the advent of the 4th industrial revolution, various technologies have received much attention. Technologies related to the 4th industry include the Internet of Things (IoT), big data, artificial intelligence, virtual reality (VR), 3D printers, and robotics, and these technologies are often converged. In particular, the robotics field is combined with technologies such as big data, artificial intelligence, VR, and digital twins. Accordingly, much research using robotics is being conducted, which is applied to distribution, airports, hotels, restaurants, and transportation fields. In the given situation, research on human-robot interaction is attracting attention, but it has not yet reached the level of user satisfaction. However, research on robots capable of perfect communication is steadily being conducted, and it is expected that it will be able to replace human emotional labor. Therefore, it is necessary to discuss whether the current human-robot interaction technology can be applied to business. To this end, this study first examines the trend of human-robot interaction technology. Second, we compare LDA (Latent Dirichlet Allocation) topic modeling and BERTopic topic modeling methods. As a result, we found that the concept of human-robot interaction and basic interaction was discussed in the studies from 1992 to 2002. From 2003 to 2012, many studies on social expression were conducted, and studies related to judgment such as face detection and recognition were conducted. In the studies from 2013 to 2022, service topics such as elderly nursing, education, and autism treatment appeared, and research on social expression continued. However, it seems that it has not yet reached the level that can be applied to business. As a result of comparing LDA (Latent Dirichlet Allocation) topic modeling and the BERTopic topic modeling method, it was confirmed that BERTopic is a superior method to LDA.

Emotion Classification of User's Utterance for a Dialogue System (대화 시스템을 위한 사용자 발화 문장의 감정 분류)

  • Kang, Sang-Woo;Park, Hong-Min;Seo, Jung-Yun
    • Korean Journal of Cognitive Science
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    • v.21 no.4
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    • pp.459-480
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    • 2010
  • A dialogue system includes various morphological analyses for recognizing a user's intention from the user's utterances. However, a user can represent various intentions via emotional states in addition to morphological expressions. Thus, a user's emotion recognition can analyze a user's intention in various manners. This paper presents a new method to automatically recognize a user's emotion for a dialogue system. For general emotions, we define nine categories using a psychological approach. For an optimal feature set, we organize a combination of sentential, a priori, and context features. Then, we employ a support vector machine (SVM) that has been widely used in various learning tasks to automatically classify a user's emotions. The experiment results show that our method has a 62.8% F-measure, 15% higher than the reference system.

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The Effect of Characteristics of Social Intelligence Robots on Satisfaction and Intention to Use: Focused on User of Single Person Households (소셜 지능로봇의 특성이 만족과 사용의도에 미치는 영향: 1인 가구 소셜 지능로봇 사용자를 중심으로)

  • Jeon, Gyuri;Lee, Chaehyun;Jung, Sungmi;Choi, Jeongil
    • Journal of Korean Society for Quality Management
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    • v.52 no.1
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    • pp.95-113
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    • 2024
  • Purpose: This study focused on the societal changes associated with the entry into an ultra-aged society and the increase in single-person households. The core objective of this research is to investigate how social intelligent robots can bring about positive changes in the lives of individuals in single-person households and how such changes influence user satisfaction and the intention to use these robots. Methods: The study employed a cross-sectional analysis using a structural equation model. A survey designed to assess the impact of social intelligent robots' characteristics, such as perceived encouragement, empathy, presence, appearance, and attachment, on user satisfaction and usage intentions was conducted. Data were collected from a total of 335 users and analyzed using the structural equation model. Results: In the characteristics of social intelligent robots for single-person households, it was found that empathy, presence, and attachment significantly influenced satisfaction, while perceived encouragement, empathy, and attachment significantly influenced usage intentions. The research results indicate differences between enhancing user satisfaction and increasing the intention to use social intelligent robots. The findings suggest the essential need for a user-centric approach in the design and development of social intelligent robots. Additionally, it was observed that emotional support plays a crucial role in users' experiences with social intelligent robots. Conclusion: This study verified the impact of social intelligent robots on satisfaction and usage intentions based on users' experiences. It examined the influence of linguistic, visual, and personal characteristics of robots on user experiences, providing insights into how technological and human aspects of social intelligent robots interact to shape user satisfaction and usage intentions. Consequently, the study confirmed that social intelligent robots can bring positive changes to human life, emphasizing the necessity for the advancement of robot technology in a human-centric direction.

Relationship between the Level of Depression and Facial EMG Responses Induced by Humor among Children (유머에 의해 유발된 아동의 안면근육반응과 우울 수준과의 관계)

  • Jang, Eun-Hye;Lee, Ju-Ok;Sohn, Sun-Ju;Lee, Young-Chang;Sohn, Jin-Hun
    • Science of Emotion and Sensibility
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    • v.13 no.1
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    • pp.33-40
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    • 2010
  • The study is to examine relationship between the level of depression and facial EMG responses during the humor condition. Forty-three children(age range 22-49 years) participated in the study. The Korean Personality Inventory for Children(KPI-C) was used to measure the level of depression in children. While children were presented to audio-visual film clip inducing humor, facial EMG were measured on their faces(bilateral corrugators and orbicularis). A baseline state was measured during 60 seconds before the presentation of the stimulus, i.e., emotional state lasting 120 seconds. Participants were asked to report the intensity of their experienced emotion. The results of emotion assessment showed 95.3% appropriateness and 3.81 intensity on the 5 points Likert scale). Facial EMG showed a significant increase while participants experiencing humor compared to baseline state. Additionally, the result showed a negative correlation between right corrugator responses and the level of depression. The study findings showed the more children experienced depression, the less facial EMG activity they had while experiencing humor.

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Interaction Ritual Interpretation of AI Robot in the TV Show (드라마<굿 플레이스>속 인공지능 로봇의 상호작용 의례적 해석)

  • Chu, Mi-Sun;Ryu, Seoung-Ho
    • The Journal of the Korea Contents Association
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    • v.21 no.5
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    • pp.70-83
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    • 2021
  • The issue of predicting the relationship between humans and AI robots is a 'strong AI' problem. Many experts predict the tragic ending which is a strong AI with superior thinking ability than humans will conquer humans. Due to the expectations of AI robots are projected onto media, the 'morally good AI' that meets human expectations is an important issue. However, the demand for good AI and the realization of perfect technology is not limited to machines. Rather, it appears as a result of putting all responsibility on humans, driving humans into immoral beings and turning them into human and human problems, which is resulting in more alienation and discrimination. As such, the result of technology interacts with the human being used and its properties are determined and developed according to the reaction. This again affects humans. Therefore, AI technology that considers human emotions in consideration of interaction is also important. Therefore, this study will clarify the process that the demand for 'Good AI' in the relationship of AI to humans with Randall Collins' Interaction Ritual Chain. Emotional energy in Interaction Ritual Chain has explained the formation of human bonds. Also, the methodology is a type of thinking experiment and explained through Janet and surrounding characters in the TV show .