Toward a linguistically grounded dialog model for chatbot design

The increasing interest in various types of conversational interfaces has been supported by a progressive standardization of the technological frameworks used to build them. However, the landscape of available methodological frameworks for designing conversations is much more fragmented. We propose a highly generalizable methodology for designing conversational flows rooted in a functionalist-pragmatics perspective, with an explicit adherence to a conversationalist approach. In parallel, we elaborate a practical-procedural workflow for undertaking chatbots projects in which we situate the theoretical starting point. At last, we elaborate a general case- study on which we transpose the identified approach in Italian language and using one of the most authoritative NLU platforms

헬스케어를 위한 대화형 인공지능의 모사된 페르소나 디자인 및 사용자 경험 연구

학위논문(박사) -- 서울대학교대학원 : 인문대학 협동과정 인지과학전공, 2021.8. 이준환.디지털 헬스케어(Digital Healthcare) 기술의 발전은 일상 헬스케어 영역에서의 혁신을 주도 하고 있다. 이는 의학 전문가들의 정확한 진단, 질병의 치료를 도울 뿐만 아니라 사용자가 스스로 일상에서 자기관리를 할 수 있도록 돕는다. 디지털 헬스케어 기술의 대표적인 목표 중 하나는 효과적으로 헬스케어 서비스를 개인화 시키는 것인데, 이러한 측면에서 대화형 인공지능(Conversational AI)은 사용하기 쉽고 효율적인 비용으로 개인화된 서비스를 제공할 수 있기에 주목받고 있다. 기존의 개인화된 케어 서비스들의 경우는 대부분 의료기관의 질병치료 서비스들에 포함되었는데, 대화형 인공지능은 이러한 개인화된 케어 서비스의 영역을 일상에서의 질병 예방을 위한 관리로 확장하는데 기여한다. 일대일 대화를 통해 맞춤형 교육, 테라피, 그외의 관련 정보 등을 제공할 수 있다는 측면에서 일상 헬스케어에 적합한 디지털 헬스케어 기술로의 활용도가 높다. 이러한 이점으로 인해 다양한 역할을 가진 대화형 인공지능들의 개발이 이루어지고 있다. 그러나, 이러한 대화형 인공지능들에게 사용자의 선호도에 적합한 페르소나를 부여하는 연구는 드물게 이루어 지고 있다. 대화형 인공지능의 주요 기능인 자연어 기반 상호작용은 CASA 패러다임(CASA Paradigm)에서 제기하는 사용자가 시스템을 의인화하는 경향을 높인다. 때문에 페르소나에 대한 사용자의 선호도가 지속적인 대화형 인공지능의 사용과 몰입에 영향을 미친다. 또한 대화형 인공지능의 장기적인 사용을 위해서 적절한 사용자와의 사회적, 감정적 상호작용을 디자인 해 주어야 하는데, 인지된 페르소나에 대한 사용자의 선호도가 이 과정에도 유의미한 영향을 미친다. 때문에 지속적인 참여가 결과에 큰 영향을 미치는 일상 헬스케어 영역에서 대화형 인공지능을 활용하는데 개인화된 페르소나 디자인이 긍정적인 사용자 경험 및 사용자 건강 증진의 가능성을 높일 것으로 본 연구는 가정한다. 개인화된 페르소나 디자인을 위해 사용자와 현실에서 친밀한 관계에 있는 실존인물(호스트)의 페르소나를 대화형 인공지능에 적용하고 평가하는 것이 본 연구의 핵심적인 아아디어이다. 이를 검증하기 위해서 해당 학위 논문은 총 세 가지의 세부 연구를 포함한다. 첫째는 실존인물의 페르소나 중에서도 일상 건강관리에 적합한 호스트의 페르소나를 탐색하는 연구이다. 둘째는 호스트의 페르소나를 대화형 인공지능에 적용하기 위해 고려해야 할 언어적 요소들을 정의하는 연구이다. 마지막으로는 위의 과정을 통해 개발된 실존하는 인물의 페르소나를 가진 대화형 인공지능이 일상 헬스케어 영역에서 실제 효과를 보이는지를 평가하는 연구이다. 또한 해당 학위논문은 일련의 연구들에서 발견한 결과들을 바탕으로 사용자와 친밀한 관계에 있는 페르소나를 일상 헬스케어를 위한 대화형 인공지능에 적용할 때 고려해야할 디자인 함의점들을 도출하고 가이드라인을 제시한다.Advance in digital healthcare technologies has been leading a revolution in healthcare. It has been showing the enormous potential to improve medical professionals’ ability for accurate diagnosis, disease treatment, and the users’ daily self-care. Since the recent transformation of digital healthcare aims to provide effective personalized health services, Conversational AI (CA) is being highlighted as an easy-to-use and cost-effective means to deliver personalized services. Particularly, CA is gaining attention as a mean for personalized care by ingraining positive self-care behavior in a daily manner while previous methods for personalized care are focusing on the medical context. CA expands the boundary of personalized care by enabling one-to-one tailored conversation to deliver health education and healthcare therapies. Due to CA's opportunities as a method for personalized care, it has been implemented with various types of roles including CA for diagnosis, CA for prevention, and CA for therapy. However, there lacks study on the personalization of healthcare CA to meet user's preferences on the CA's persona. Even though the CASA paradigm has been applied to previous studies designing and evaluating the human-likeness of CA, few healthcare CAs personalize its human-like persona except some CAs for mental health therapy. Moreover, there exists the need to improve user experience by increasing social and emotional interaction between the user and the CA. Therefore, designing an acceptable and personalized persona of CA should be also considered to make users to be engaged in the healthcare task with the CA. In this manner, the thesis suggests an idea of applying the persona of the person who is in a close relationship with the user to the conversational CA for daily healthcare as a strategy for persona personalization. The main hypothesis is the idea of applying a close person's persona would improve user engagement. To investigate the hypothesis, the thesis explores if dynamics derived from the social relationship in the real world can be implemented to the relationship between the user and the CA with the persona of a close person. To explore opportunities and challenges of the research idea, series of studies were conducted to (1) explore appropriate host whose persona would be implemented to healthcare CA, (2) define linguistic characteristics to consider when applying the persona of a close person to the CA, and (3)implement CA with the persona of a close person to major lifestyle domains. Based on findings, the thesis provides design guidelines for healthcare CA with the persona of the real person who is in a close relationship with the user.Abstract 1 1 Introduction 12 2 Literature Review 18 2.1 Roles of CA in Healthcare 18 2.2 Personalization in Healthcare CA 23 2.3 Persona Design CA 25 2.4 Methods for Designing Chatbot’s Dialogue Style 30 2.4.1 Wizard of Oz Method 32 2.4.2 Analyzing Dialogue Data with NLP 33 2.4.3 Participatory Design 35 2.4.4 Crowdsourcing 37 3 Goal of the Study 39 4 Study 1. Exploring Candidate Persona for CA 43 4.1 Related Work 44 4.1.1 Need for Support in Daily Healthcare 44 4.1.2 Applying Persona to Text-based CA 45 4.2 Research Questions 47 4.3 Method 48 4.3.1 Wizard of Oz Study 49 4.3.2 Survey Measurement 52 4.3.3 Post Interview 54 4.3.4 Analysis 54 4.4 Results 55 4.4.1 System Acceptance 56 4.4.2 Perceived Trustfulness and Perceived Intimacy 57 4.4.3 Predictive Power of Corresponding Variables 58 4.4.4 Linguistic Factors Affecting User Perception 58 4.5 Implications 60 5 Study 2. Linguistic Characteristics to Consider When Applying Close Person’s Persona to a Text-based Agent 63 5.1 Related Work 64 5.1.1 Linguistic Characteristics and Persona Perception 64 5.1.2 Language Component 66 5.2 Research Questions 68 5.3 Method 69 5.3.1 Modified Wizard of Oz Study 69 5.3.2 Survey 72 5.4 Results 73 5.4.1 Linguistic Characteristics 73 5.4.2 Priority of Linguistic Characteristics 80 5.4.3 Differences between language Component 82 5.5 Implications 82 6 Study3.Implementation on Lifestyle Domains 85 6.1 Related Work 86 6.1.1 Family as Effective Healthcare Provider 86 6.1.2 Chatbots Promoting Healthy Lifestyle 87 6.2 Research questions 94 6.3 Implementing Persona of Family Member 95 6.3.1 Domains of Implementation 96 6.3.2 Measurements Used in the Study 97 6.4 Experiment 1: Food Journaling Chatbot 100 6.4.1 Method 100 6.4.2 Results 111 6.5 Experiment 2: Physical Activity Intervention 128 6.5.1 Method 131 6.5.2 Results 140 6.6 Experiment 3: Chatbot for Coping Stress 149 6.6.1 Method 151 6.6.2 Results 158 6.7 Implications from Domain Experiments 169 6.7.1 Comparing User Experience 170 6.7.2 Comparing User Perception 174 6.7.3 Implications from Study 3 183 7 Discussion 192 7.1 Design Guidelines 193 7.2 Ethical Considerations 200 7.3 Limitations 206 8 Conclusion 210 References 212 Appendix 252 국문초록 262박

Subtitling Humour from the Perspective of Relevance Theory: The Office in Traditional Chinese

Subtitling the scenes containing humorous utterances in cinematic-televisual productions encounters a myriad of challenges, because the subtitler has to face the technical constraints that characterise the professional subtitling environment and the cultural barriers when reproducing humorous utterances for viewers inhabiting another culture. Past studies tend to explore more limited humour-related areas, which means that a more comprehensive picture of this specialised field is missing. The current research investigates the subtitling of humour, drawing on the framework of relevance theory and the British sitcom The Office, translated from English dialogue into Traditional Chinese subtitles. This research enquires into whether or not relevance theory can explain the subtitling strategies activated to deal with various humorous utterances in the sitcom, and, if so, to what extent. The English-Chinese Corpus of The Office (ECCO), which contains sample texts, media files and annotations, has been constructed to perform an empirical study. To enrich the corpus with valuable annotations, a typology of humour has been developed based on the concept of frame, and a taxonomy of subtitling strategies has also been proposed. The quantitative analysis demonstrates that the principle of relevance is the main benchmark for the choice of a subtitling micro-strategy within any given macro-strategy. With the chi-square test, it further proves the existence of a statistically significant association between humour types/frames and subtitling strategies at the global level. The qualitative analysis shows that the principle of relevance can operate in a subtle way, in which the subtitler invests more cognitive efforts to enhance the acceptability of subtitles. It also develops three levels of mutual dependency between the two variables, from strong, weak to null, to classify different examples. Overall, this study improves our understanding of humour translation and can facilitate a change in the curricula of translator training

An Investigation of Digital Reference Interviews: A Dialogue Act Approach

The rapid increase of computer-mediated communications (CMCs) in various forms such as micro-blogging (e.g. Twitter), online chatting (e.g. digital reference) and community- based question-answering services (e.g. Yahoo! Answers) characterizes a recent trend in web technologies, often referred to as the social web. This trend highlights the importance of supporting linguistic interactions in people\u27s online information-seeking activities in daily life - something that the web search engines still lack because of the complexity of this hu- man behavior. The presented research consists of an investigation of the information-seeking behavior of digital reference services through analysis of discourse semantics, called dialogue acts, and experimentation of automatic identification of dialogue acts using machine-learning techniques. The data was an online chat reference transaction archive, provided by the Online Computing Library Center (OCLC). Findings of the discourse analysis include supporting evidence of some of the existing theories of the information-seeking behavior. They also suggest a new way of analyzing the progress of information-seeking interactions using dia- logue act analysis. The machine learning experimentation produced promising results and demonstrated the possibility of practical applications of the DA analysis for further research across disciplines