Detection of Adolescent Depression from Speech Using Optimised Spectral Roll-Off Parameters

Abstract

The purpose of this paper is to examine adolescent depression detection from a clinical database of 63 adolescents (29 depressed and 34 non-depressed) interacting with a parent. A range of spectral roll-off parameters was investigated to observe an association of the frequencyenergy relationship in relation to depression. The spectral roll-off range improved depression classification rates compared to the best individual roll-off parameter. Further improvement was accomplished using a 2-stage mRMR/SVM feature selection approach to optimize a roll-off parameters subset