研究对话中性格感知如何随情境变化，发现压力场景更易反映神经质特质。
Assessment of Personality Dimensions Across Situations in Dyadic Role-Play Scenarios
- 对比中性面试与压力客户互动中的语音特征与性格感知关系
- 压力情境下性格判断准确率更高，尤其神经质维度
- 音量、声强等声学特征比说话人嵌入更有效
先前研究表明，用户更偏好与其性格匹配的辅助技术。这激发了自动性格感知（APP）的研究兴趣，旨在预测个体被感知的性格特质。以往的APP研究将性格视为不受情境影响的静态特征，但心理学研究显示，感知性格会随情境变化。本研究考察了在两种工作情境（中性面试与压力客户互动）中，对话语音与被感知性格的关系。主要发现：1）不同互动中感知性格存在显著差异；2）在中性情境中，音量、声强和频谱通量特征可指示外向性、宜人性、尽责性和开放性；而在压力情境中，这些特征与神经质相关；3）手工设计的声学特征和非语言特征在性格推断上优于说话人嵌入；4）压力互动对神经质的预测力更强，符合现有心理学研究。
原文摘要 · Abstract (English)
Prior research indicates that users prefer assistive technologies whose personalities align with their own. This has sparked interest in automatic personality perception (APP), which aims to predict an individual's perceived personality traits. Previous studies in APP have treated personalities as static traits, independent of context. However, perceived personalities can vary by context and situation as shown in psychological research. In this study, we investigate the relationship between conversational speech and perceived personality for participants engaged in two work situations (a neutral interview and a stressful client interaction). Our key findings are: 1) perceived personalities differ significantly across interactions, 2) loudness, sound level, and spectral flux features are indicative of perceived extraversion, agreeableness, conscientiousness, and openness in neutral interactions, while neuroticism correlates with these features in stressful contexts, 3) handcrafted acoustic features and non-verbal features outperform speaker embeddings in inference of perceived personality, and 4) stressful interactions are more predictive of neuroticism, aligning with existing psychological research.
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