Enhancing speech-based depression detection through gender dependent vowel-level formant features

Abstract

Depression has been consistently linked with alterations in speech motor control characterised by changes in formant dynamics. However, potential differences in the manifestation of depression between male and female speech have not been fully realised or explored. This paper considers speech-based depression classification using gender dependant features and classifiers. Presented key observations reveal gender differences in the effect of depression on vowel-level formant features. Considering this observation, we also show that a small set of handcrafted gender dependent formant features can outperform acoustic-only based features (on two state-of-the-art acoustic features sets) when performing two-class (depressed and non-depressed) classification.