Design Thinking for Developing a Case-Based Reasoning Emotional Robot: In the Scenario of Interactive Interview

• Main Authors: Shu-Xuan Lin, 林書瑄
• Other Authors: Sheng-Ming Wang
• Format: Others
• Language: zh-TW
• Published: 2017
• Online Access: http://ndltd.ncl.edu.tw/handle/h6tpad

碩士 === 國立臺北科技大學 === 互動媒體設計研究所 === 105 === As the application of design and technology has become more interdisciplinary and integrated, the development of interactive service robots (ISRs), which are designed according to unique situational requirements, has emerged as a popular trend. Research has shown that if affective computing technology and machine learning mechanisms can be introduced to enhance interaction and feedback between ISRs and users, ISRs can better satisfy the needs of a greater number of people. In addition, they may be better aligned with both the service context and the future development of innovative services. Based on an interdisciplinary integration framework, this study combines the concept and method of design thinking, emotion-detection technology, and case-based reasoning (CBR) to simulate the service situation of an interview, and thus to develop a prototype emotion-sensing robot (ESR) system. The results of the experiment were then used to analyze the effectiveness of integrating corresponding technologies as well as the value, utility, and affordance of the developed system. The process of empirical verification was divided into two steps. First, a pilot test was adopted to create a basic database based on a simulated case, and initial weights were assigned to each attributing factor. Next, the prototype system was tested using participants from various fields of expertise and backgrounds, and differences in interaction and feedback between participants and the system were analyzed. These differences were then introduced into the system as references to modify the weights of each attributing factor when testing with participants from different professional areas. Empirical results showed that the emotional responses of participants during the simulated interview were consistent with those hypothesized in the user journey map. The results of the correlation analysis revealed that blink rate was a significant determinant of the perception of tension. The predictive power in detecting facial expressions, analysis of semantic emotions, and accuracy of keyword matching related to perception of tension appeared to differ significantly between participants from different fields of expertise and backgrounds. Therefore, assigning more weight to detection factors that correlate specifically with participant emotions helps to reveal the utility of the prototype of the ESR system. In addition to applying design thinking to guide the development of ESR technology, the main contribution of this research is that it creates an integrated model for innovative service and the future development of emotion-sensing applications. In summary, this study constructed an ESR prototype and validated its worth as an application by integrating and testing core emotion-detection technologies. The ESR developed based using an interdisciplinary approach is able to connect user needs and the application of technology to the development of corresponding functions. In addition, our research offers a direction for the further development of innovative robotic services. Furthermore, this study introduced CBR analysis to establish a link between an interactive service context, the professional backgrounds of users, and an emotion-sensing evaluation system. Despite meeting both user requirements and user-centered design requirements, as well as demonstrating the feasibility of the system, further improvements can be made. Future studies are necessary to enrich the cases in the database of CBR system and establish a foundation of machine learning principles for ESRs.