设计有效的面试聊天机器人：自动聊天机器人分析和聊天机器人设计建议生成
Designing Effective Interview Chatbots: Automatic Chatbot Profiling and Design Suggestion Generation for Chatbot Debugging
摘要：
最近的研究表明了面试聊天机器人在信息获取方面的有效性。然而，设计一个有效的面试聊天机器人并不简单。很少有工具可以帮助设计师设计，评估和迭代改进面试聊天机器人。基于形成性研究和文献综述，我们提出了一个量化面试聊天机器人性能的计算框架。结合该框架，我们开发了iChatProfile，这是一种辅助聊天机器人设计工具，可以自动生成具有量化性能指标的面试聊天机器人配置文件，并根据这些指标提供改进聊天机器人的设计建议。为了验证iChatProfile的有效性，我们设计并进行了一项受试者间研究，比较了使用或不使用iChatProfile设计的10个面试聊天机器人的表现。基于10个聊天机器人和1349个用户之间的实时聊天，我们的结果表明，iChatProfile帮助设计师构建了更有效的面试聊天机器人，提高了面试质量和用户体验。
英文摘要：
Recent studies show the effectiveness of interview chatbots for information elicitation. However, designing an effective interview chatbot is non-trivial. Few tools exist to help designers design, evaluate, and improve an interview chatbot iteratively. Based on a formative study and literature reviews, we propose a computational framework for quantifying the performance of interview chatbots. Incorporating the framework, we have developed iChatProfile, an assistive chatbot design tool that can automatically generate a profile of an interview chatbot with quantified performance metrics and offer design suggestions for improving the chatbot based on such metrics. To validate the effectiveness of iChatProfile, we designed and conducted a between-subject study that compared the performance of 10 interview chatbots designed with or without using iChatProfile. Based on the live chats between the 10 chatbots and 1349 users, our results show that iChatProfile helped the designers build significantly more effective interview chatbots, improving both interview quality and user experience.
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。
