PersonalityScanner：探索基于虚拟现实中多模态信号的人格评估的有效性
PersonalityScanner: Exploring the Validity of Personality Assessment Based on Multimodal Signals in Virtual Reality
AI总结：
本文开发了虚拟现实模拟器PersonalityScanner，通过构建沉浸式交互环境收集包含十种模态的同步多模态数据集，以模拟日常行为并刺激认知过程，从而克服传统问卷的客观性不足，系统验证了多模态信号在人格评估中的有效性与优越性能。
摘要：
人类认知显著影响表达出的行为，并与真实的人格特质内在相关。人格评估在心理学、教育、社交媒体等多个领域发挥着关键作用。然而，传统的自我报告问卷只能基于个人愿意和能够披露的内容提供数据，从而缺乏客观性。此外，自动化测量和同伴评估需要大量的人力和资源。在本文中，鉴于虚拟现实（VR）技术的优势，我们开发了一个VR模拟器——PersonalityScanner，以基于沉浸式和交互式的模拟环境刺激认知过程并模拟日常行为，参与者在其中执行一系列引人入胜的任务，这些任务构成了上班第一天的自然故事。通过该模拟器，我们收集了一个包含十种模态的同步多模态数据集，包括第一/第三人称视频、音频、文本、眼动追踪、面部微表情、姿态、深度数据、日志和惯性测量单元。通过系统地检验不同模态在揭示人格方面的贡献，我们证明了PersonalityScanner的卓越性能和有效性。
英文摘要：
Human cognition significantly influences expressed behavior and is intrinsically tied to authentic personality traits. Personality assessment plays a pivotal role in various fields, including psychology, education, social media, etc. However, traditional self-report questionnaires can only provide data based on what individuals are willing and able to disclose, thereby lacking objective. Moreover, automated measurements and peer assessments demand significant human effort and resources. In this paper, given the advantages of the Virtual Reality (VR) technique, we develop a VR simulator -- PersonalityScanner, to stimulate cognitive processes and simulate daily behaviors based on an immersive and interactive simulation environment, in which participants carry out a battery of engaging tasks that formulate a natural story of first-day at work. Through this simulator, we collect a synchronous multi-modal dataset with ten modalities, including first/third-person video, audio, text, eye tracking, facial microexpression, pose, depth data, log, and inertial measurement unit. By systematically examining the contributions of different modalities on revealing personality, we demonstrate the superior performance and effectiveness of PersonalityScanner.
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。
