低成本非生成式对话系统，用于标准化访谈数据收集。
ISCA: A Framework for Interview-Style Conversational Agents
- 基于可在线配置的管理面板，无需编码即可创建新访谈
- 支持定量分析与定性数据采集，适用于态度或行为变化追踪
- 开源框架，适合研究者快速构建访谈类对话应用
我们提出一种低计算成本的非生成式系统，用于实现面试风格的对话智能体，可在受控交互中促进定性数据收集与定量分析。应用场景包括追踪态度形成或行为改变，尤其在需要标准化对话流程时。通过在线管理面板，用户可轻松调整系统以创建新访谈，无需编程。本文展示两个案例：一是针对新冠疫情的表达性访谈系统，二是关于新兴神经技术公众意见的半结构化访谈。代码开源，支持他人在此基础上扩展功能。
原文摘要 · Abstract (English)
We present a low-compute non-generative system for implementing interview-style conversational agents which can be used to facilitate qualitative data collection through controlled interactions and quantitative analysis. Use cases include applications to tracking attitude formation or behavior change, where control or standardization over the conversational flow is desired. We show how our system can be easily adjusted through an online administrative panel to create new interviews, making the tool accessible without coding. Two case studies are presented as example applications, one regarding the Expressive Interviewing system for COVID-19 and the other a semi-structured interview to survey public opinion on emerging neurotechnology. Our code is open-source, allowing others to build off of our work and develop extensions for additional functionality.
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