Emotion Detection in Law Enforcement Interviews

Understanding the factors that lead or contribute to emotional instability in highly motivated high-conflict dialogues such as law enforcement interviews can be of crucial importance. In this paper, we extract psycholinguistic features to assess emotional stability scale development and identify patterns that are relevant to emotional breakdown. To this end, we utilize zero-shot text classification to investigate the temporal evolution of emotion during law enforcement interviews. We conduct ex-tensive experiments using publicly available police interrogation transcripts. Our results are promising and suggest avenues for future research.