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研究生:涂倫愷
研究生(外文):Tu, Kevin L.K.
論文名稱:發展具情緒分析能力之多輪智慧聊天機器人—以三方對談學生諮商系統為例
論文名稱(外文):Development of a multi-turn dialogue chatbot system: A case of trilateral virtual reality student counselling and communication system
指導教授:張瑞芬張瑞芬引用關係
指導教授(外文):Trappey, Amy J. C.
口試委員:黃雪玲王東美
口試委員(外文):Hwang, Sheue-LingWang, Tong-Mei
口試日期:2023-06-08
學位類別:碩士
校院名稱:國立清華大學
系所名稱:工業工程與工程管理學系
學門:工程學門
學類:工業工程學類
論文種類:學術論文
論文出版年:2023
畢業學年度:111
語文別:英文
論文頁數:98
中文關鍵詞:學校壓力虛擬實境心理諮商聊天機器人情緒理解虛擬治療
外文關鍵詞:School stressesOnline counselingVirtual realityVirtual psychotherapyCounseling chatbotConversational sentiment analysis
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在現今資訊爆炸及個人意識抬頭的年代,學生面臨比以往更多的壓力,例如學業、家庭、朋友、工作以及財務等方面問題,不同問題也有越來越複雜的趨勢。有些學生因而顯得不知所措、不知道該如何面對壓力、不知道該如何嘗試自我解決或是紓解壓力。長期微小壓力的累積,可能在某一刻開始造成學生巨大的困擾,諸如頭痛、失眠、飲食不正常、焦慮、憂鬱、反社會性格、甚至自殺傾向。若不加以注意及追蹤,等到造成不可逆的結果時,一切都為時已晚。在全國大專院校中,儘管設有輔導室提供心理諮商服務,但迫於資源分布不均,諮商師供不應求,預約常需要等候,使得部分學生無法及時得到協助。為解決這些問題,本研究開發一個三方對談學生諮商系統,旨在提供即時以及讓學生無壓力接受心理諮商的平台。本研究創新之處在於提出三方諮商的框架,使系統可以同時容納包含學生、諮商師、以及聊天機器人共同在虛擬實境(VR)辦公室場景進行諮商。本研究也設計容許透過網頁來訪問本系統,使得沒有VR的環境下也能進行諮商。聊天機器人包含三大模組:自然語言理解(NLU)、對話管理(DM)、以及自然語言生成(NLG)。聊天機器人事先加以訓練使用者意圖包含心理問題及情緒的範例、多種諮商情境流程、以及常見學生心理問題與回答(FAQs),使得機器人與學生之間多輪諮商對話得以進行,機器人能理解學生的心理問題及情緒,並產生最貼切的建議。本研究特地設計讓諮商師能夠全程參與諮商過程,隨時提出自己的意見,協助補充聊天機器人的回答,使得學生可以得到最好的治療。本研究也特別將原本聊天機器人針對相同心理問題而給予學生的回答,去進行改寫,使得每次回答都不盡相同,讓諮商體驗更臻完善。最後本研究系統驗證包含量化與質性研究。量化研究針對聊天機器人每種模組,使用多種模型進行績效研究,來選出最好的模型,作為本研究聊天機器人各個模組的模型。質性研究則透過訪問具學校諮商經驗的諮商師,詢問諮商師的專業意見、比較本研究系統與傳統諮商的差異、說明系統未來改善建議、並提供未來學生諮商系統的發展指引。
College students experience heightened stress during the era of information overload. This stress stems from various sources, such as studies, family, friends, work, and finance, and has become increasingly prevalent. However, counseling resources are often limited, and students require prompt and multiple therapy sessions to avoid making matters worse. To address these challenges, this study proposes a trilateral counseling system consisting of two chatrooms and a chatbot. The novelty of this system is trilateral conversations, which involve a student, a counselor, and the chatbot, having therapy sessions together within a virtual reality (VR) chatroom. Additionally, a web-based chatroom is available for situations where VR access is inconvenient. Our chatbot, equipped with three crucial modules, including natural language understanding (NLU), dialogue management (DM), and natural language generation (NLG), are able to initiate multi-turn conversations with the student. Its knowledge base is built upon frequently asked questions (FAQs) in psychological counseling. Thanks to these three modules, the system effectively identifies student issues and emotions during conversations, allows therapy sessions to follow predetermined scenarios, and provides timely suggestions to the student. Moreover, the chatbot rephrases responses from FAQs to enhance the overall counseling experience. The counselor can oversee the therapy session and offer professional advice whenever needed. The research selects multiple model options for three modules and then evaluates their performance using metrics. The best models for each module are chosen to construct the system. Furthermore, feedback from counselors that are experienced in school counseling is obtained to gather their opinions on the system and provide insights for further research development.
摘要 I
Abstract II
Table of Contents III
List of Figures V
List of Tables VI
1 Introduction 1
1.1 Research background 1
1.2 Research purpose 2
1.3 Research framework 3
2 Literature Review 5
2.1 Psychotherapy used for student stress 5
2.2 Healthcare applications using immersive technologies 7
2.3 Advanced chatbots with natural language conversation capability 10
3 System Framework and Key Methodologies 17
3.1 System framework 17
3.2 Avatar-based chatroom jointed by student, counselor, and chatbot 18
3.3 Empathy-centric counseling NLP chatbot 22
4 System Implementation 27
4.1 Chatroom interface 27
4.2 Preparing dataset 28
4.3 Natural language understanding (NLU) 32
4.4 Dialogue management (DM) 33
4.5 Natural language generation (NLG) 34
4.6 Counseling case scenarios and demonstrations 36
5 Prototype System Verification and Evaluation 45
5.1 Module program testing 45
5.2 Evaluation feedback from domain experts 56
6 Conclusions 65
References 69
Appendix A 76
Appendix B 78
Appendix C 81
Appendix D 84
Appendix E 89
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