开源工具让本地大模型驱动社交机器人快速上手
SRWToolkit: An Open Source Wizard of Oz Toolkit to Create Social Robotic Avatars
- 基于网页的魔术师式工具，支持多模态交互
- 11人小规模测试显示易用性高、用户信任度好
- 适合研究人机交互的学者快速定制机器人角色
我们提出SRWToolkit，一个开源的魔术师式（Wizard of Oz）工具包，用于快速原型化由本地大语言模型（LLMs）驱动的社交机器人化身。该网页工具包支持文本输入、按钮触发语音及唤醒词命令的多模态交互，通过直观控制面板实时配置化身外观、行为、语言与声音。相比依赖云端大模型服务的先前工作，SRWToolkit强调模块化设计，通过本地大模型推理实现设备端运行。在小规模用户研究（n=11）中，参与者创建并互动了多种机器人角色（如医院接待员、数学教师、驾驶助手），结果表明该工具在可用性、信任度和用户体验方面表现良好。该工具可高效支持研究人员按需定制机器人角色，推动人机交互领域的可扩展研究。
原文摘要 · Abstract (English)
We present SRWToolkit, an open-source Wizard of Oz toolkit designed to facilitate the rapid prototyping of social robotic avatars powered by local large language models (LLMs). Our web-based toolkit enables multimodal interaction through text input, button-activated speech, and wake-word command. The toolkit offers real-time configuration of avatar appearance, behavior, language, and voice via an intuitive control panel. In contrast to prior works that rely on cloud-based LLM services, SRWToolkit emphasizes modularity and ensures on-device functionality through local LLM inference. In our small-scale user study ($n=11$), participants created and interacted with diverse robotic roles (hospital receptionist, mathematics teacher, and driving assistant), which demonstrated positive outcomes in the toolkit's usability, trust, and user experience. The toolkit enables rapid and efficient development of robot characters customized to researchers' needs, supporting scalable research in human-robot interaction.
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