静态与自适应主动式语音智能体的感知比较
Comparing Perceptions of Static and Adaptive Proactive Speech Agents
AI总结：
本研究对比自适应与静态主动式语音智能体的用户感知，发现以人类打断行为为模型的自适应智能体反而被认为对话表现更差、打断方式不当，源于其社交得体性和互动一致性不足。
摘要：
越来越多关于语音打断的文献描述了人们如何用语音打断他人，但这些行为尚未被应用到会实施打断的人工智能体设计中。本研究将一款能根据打断场景的紧急程度以及被打断的当前任务难度调整语音的原型主动式语音智能体，与不具备该调整能力的静态主动式智能体的用户感知进行对比。研究假设，以人类语音打断行为为模型的自适应主动语音会让使用者的伙伴模型认为，该主动智能体比静态智能体是更出色的对话伙伴，且自适应智能体发起的打断会被判定为时机更恰当、提问更合适。然而这些假设均被推翻：定量分析显示，参与者认为自适应智能体是比静态智能体更差的对话伙伴，其打断方式也更不合适。定性分析揭示了这一意外发现的原因：参与者认为自适应智能体的社交得体性更差，且互动中的一致性不如静态智能体。
英文摘要：
A growing literature on speech interruptions describes how people interrupt one another with speech, but these behaviours have not yet been implemented in the design of artificial agents which interrupt. Perceptions of a prototype proactive speech agent which adapts its speech to both urgency and to the difficulty of the ongoing task it interrupts are compared against perceptions of a static proactive agent which does not. The study hypothesises that adaptive proactive speech modelled on human speech interruptions will lead to partner models which consider the proactive agent as a stronger conversational partner than a static agent, and that interruptions initiated by an adaptive agent will be judged as better timed and more appropriately asked. These hypotheses are all rejected however, as quantitative analysis reveals that participants view the adaptive agent as a poorer dialogue partner than the static agent and as less appropriate in the style it interrupts. Qualitative analysis sheds light on the source of this surprising finding, as participants see the adaptive agent as less socially appropriate and as less consistent in its interactions than the static agent.
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。
