Multimodal Personalized Depression Detection
Deep Learning
Multimodal Learning
Affective Computing
Fusing voice, facial cues, and personal attributes to predict depression level using attention-based deep learning (MPDD Challenge @ ACM Multimedia 2025).
Built a multimodal, personalized depression detection system that fuses voice, facial cues, and personal attributes to predict depression level using attention-based deep learning, developed for the MPDD Challenge @ ACM Multimedia 2025.