A Multimodal Depression Consultation Dataset of Speech and Text with HAMD-17 Assessments, Parallel Data of Depression Consultation and Hamilton Depression Rating Scale (PDCH)

This is exacerbated by a critical shortfall in mental health professionals, highlighting an urgent call for innovative approaches. The advancement of Artificial Intelligence (AI), particularly Large Language Models, offers a promising solution by improving mental health diagnostics.

However, there is a lack of real data for reliable training and accurate evaluation of AI models. To this end, this paper presents a high-quality multimodal depression consultation dataset, namely Parallel Data of Depression Consultation and Hamilton Depression Rating Scale (PDCH). The dataset is constructed based on clinical consultations from Beijing Anding Hospital, which provides audio recording and transcribed text, as well as corresponding HAMD-17 scales annotated by professionals.