Speech-based depression detection models primarily learn speaker identity rather than depression biomarkers, with performance dropping sharply on unseen speakers even under adversarial training.
Each model is tested in its original form and with a DANN extension to mitigate speaker-specific information
1 Pith paper cite this work. Polarity classification is still indexing.
1
Pith paper citing it
fields
eess.AS 1years
2026 1verdicts
UNVERDICTED 1representative citing papers
citing papers explorer
-
Who is Speaking or Who is Depressed? A Controlled Study of Speaker Leakage in Speech-Based Depression Detection
Speech-based depression detection models primarily learn speaker identity rather than depression biomarkers, with performance dropping sharply on unseen speakers even under adversarial training.