情感对话智能体：理解期望与个人影响
Affective Conversational Agents: Understanding Expectations and Personal Influences
AI总结：
通过调查745名受访者对32个场景下AI智能体情感技能的期望与偏好，发现所需情感能力高度依赖应用语境，受情绪重评和人格特质影响，强调设计需具备适应性与情境感知。
摘要：
AI对话智能体的兴起拓宽了在各个领域增强人类能力的机会。随着这些智能体日益普及，研究不同情感能力对其性能和用户体验的影响至关重要。在本研究中，我们调查了745名受访者，以了解各类应用中对情感技能的期望与偏好。具体而言，我们评估了在32个不同场景下，对能够感知、回应和模拟情感的AI智能体的偏好。结果表明，受访者更偏好涉及人际互动、情感支持和创意任务的场景，且受到情绪重评和人格特质等因素的影响。总体而言，AI智能体中所需的情感技能在很大程度上取决于应用的语境与性质，这强调了在情感AI对话智能体设计中具备适应性和情境感知能力的必要性。
英文摘要：
The rise of AI conversational agents has broadened opportunities to enhance human capabilities across various domains. As these agents become more prevalent, it is crucial to investigate the impact of different affective abilities on their performance and user experience. In this study, we surveyed 745 respondents to understand the expectations and preferences regarding affective skills in various applications. Specifically, we assessed preferences concerning AI agents that can perceive, respond to, and simulate emotions across 32 distinct scenarios. Our results indicate a preference for scenarios that involve human interaction, emotional support, and creative tasks, with influences from factors such as emotional reappraisal and personality traits. Overall, the desired affective skills in AI agents depend largely on the application's context and nature, emphasizing the need for adaptability and context-awareness in the design of affective AI conversational agents.
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。
