AI RESEARCH
Entropy-Dominated Temporal Vocal Dynamics as Digital Biomarkers for Depression Detection
arXiv CS.AI
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ArXi:2604.26998v1 Announce Type: cross Automated depression detection often relies on static aggregation of conversational signals, potentially obscuring clinically meaningful behavioral dynamics. We investigated whether entropy-driven temporal biomarkers improve depression detection beyond standard pooled features using the DAIC-WOZ corpus.