Deep learning models extract content-agnostic voice biomarkers for depression and anxiety from a ~65k-utterance proprietary dataset, achieving 71% sensitivity and specificity when combined with lexical features.
Nithin Rao Koluguri, Taejin Park, and Boris Ginsburg
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Voice Biomarkers for Depression and Anxiety
Deep learning models extract content-agnostic voice biomarkers for depression and anxiety from a ~65k-utterance proprietary dataset, achieving 71% sensitivity and specificity when combined with lexical features.