Exploring Machine Learning and Language Models for Multimodal Depression Detection

Data were collected through semi-structured interviews conducted in hospital settings. Each participant completed standardized clinical questionnaires, including the PHQ-9 and HAMD-24 scales [27], to assess depression severity. HAMD-24 scores are used to generate labels for the binary and ternary classification tasks, while PHQ-9 scores are used for the quinary classification task. To enable a more comprehensive participant profile, additional annotations are provided, including Big five personality traits (using a 10-point scale) [15], physical health conditions, financial stress levels, and the number of cohabiting family members, see Table II.