Towards Explainable Multimodal Depression Recognition for Clinical Interviews
This episode explores research on explainable multimodal depression recognition for clinical interviews. The hosts discuss the new EMDRC task, the DAIC-Explain dataset, and two methods: the PhqMML multi-task learning framework and the PhqCoT reasoning-based approach. They conclude that these tools provide essential transparency for clinicians.