cs.AI updates on arXiv.org 07月28日 12:42
Assessment of Personality Dimensions Across Situations Using Conversational Speech
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本文探讨了语境对自动人格感知技术的影响,分析了不同语境下对话语音与人格感知的关系,发现语境对人格感知有显著影响,并提出了相关研究结论。

arXiv:2507.19137v1 Announce Type: cross Abstract: 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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自动人格感知 语境影响 人格感知 对话语音 心理学研究
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