Automatic Detection of Auditory, Visual and Physiological Parameters for the Diagnosis
of Affective Disorders
EU Funded Project Affective Mind
Automatic Speech Feature Extraction. Input: Real time PC-Speaker Audio. Processing (a) Extraction of Mel Frequency Cepstral Coefficients (MFCC). Output (b): BDI-Depression Score.
Depression Symptoms (a) Low vs. (b) High Energy Sample
Example of extraction of key figures from time-frequency diagrams of the speech signal. Shown as horizontal bars are the resonance frequencies of the vocal tract associated with jaw opening, horizontal tongue position and vocal tract tension. Vocal tract parameters provide, among other things, information on depression-associated speaker states such as sadness, fatigue depression states and comorbid anxiety states.
Work Packages, Insights and Outcomes
Overview of the Multi-Modal Depression Classification Framework
Demonstrator Prototype: Sadness Detection via Speech