探索基于情感敏感LLM的对话式AI
Exploring Emotion-Sensitive LLM-Based Conversational AI
AI总结：
本研究通过比较30名参与者使用情感敏感与不敏感的基于LLM的聊天机器人，发现情感敏感型聊天机器人虽未提升问题解决率，但能提高用户对其可信度和能力的感知，为客户服务中对话式AI的优化提供参考。
摘要：
对话式AI聊天机器人在客户服务行业中日益普及。尽管其情感发展有所改善，但它们往往缺乏真实客户服务互动的真实性或服务提供者的能力。通过在30名参与者中比较情感敏感和情感不敏感的基于LLM的聊天机器人，我们旨在探索聊天机器人的情感敏感性如何影响服务互动中的感知能力和整体客户满意度。此外，我们采用情感分析技术来分析和解释用户输入的情感内容。我们强调，即使问题解决率未受影响，情感敏感型聊天机器人的可信度和能力感知也更高。我们讨论了情感敏感型聊天机器人提高用户满意度的意义及其在支持服务中的潜在应用。
英文摘要：
Conversational AI chatbots have become increasingly common within the customer service industry. Despite improvements in their emotional development, they often lack the authenticity of real customer service interactions or the competence of service providers. By comparing emotion-sensitive and emotion-insensitive LLM-based chatbots across 30 participants, we aim to explore how emotional sensitivity in chatbots influences perceived competence and overall customer satisfaction in service interactions. Additionally, we employ sentiment analysis techniques to analyze and interpret the emotional content of user inputs. We highlight that perceptions of chatbot trustworthiness and competence were higher in the case of the emotion-sensitive chatbot, even if issue resolution rates were not affected. We discuss implications of improved user satisfaction from emotion-sensitive chatbots and potential applications in support services.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
