Prediction of major depression in adolescents using an optimized multi-channel weighted speech classification system

Abstract

This study addresses an urgent need for objective measures allowing an efficient, early prediction of risk for depression in adolescents. An early intervention preventing the onset of clinical depression could significantly reduce the social and economic burden of the disease. Previous studies have shown that acoustic speech parameters are strong indicators of full blown depression symptoms in adults and adolescents. The current study investigates the effectiveness of acoustic speech analysis and classification in prediction of depression in adolescents before the full blown symptoms become apparent. The proposed optimized multi-channel weighted speech classification (OMCWSC) method introduc..