Probabilistic Textual Time Series Depression Detection
Department of Computer Science, KTH Royal Institute of Technology（计算机科学系，皇家理工学院）；Department of Information Technology, Uppsala University（信息科技系，乌普萨拉大学）
Fabian Schmidt, Seyedehmoniba Ravan, Vladimir Vlassov
Accurate and interpretable predictions of depression severity are essential for clinical decision support, yet existing models often lack uncertainty estimates and temporal interpretability. We propose PTTSD, a Probabilistic framework for Depression Detection from clinical interview utterance sequences that predicts PHQ-8 scores while modeling calibrated uncertainty. PTTSD includes sequence-to-sequence and sequence-to-one variants, both combining LSTMs, self-attention, and residual connections with Gaussian or Student's-t output heads trained via negative log-likelihood. The sequence-to-sequence variant enables temporal analysis of how predictive confidence evolves over an interview, despite the target being a single session-level score. Evaluated on E-DAIC and DAIC-WOZ, PTTSD achieves competitive performance among text-only systems (e.g., MAE = 3.85 on E-DAIC, 3.55 on DAIC) and produces well-calibrated prediction intervals. Ablations confirm the value of attention and probabilistic modeling, while a three-part calibration analysis and qualitative case studies highlight the clinical relevance of uncertainty-aware prediction.
Investigating Acoustic-Textual Emotional Inconsistency Information for Automatic Depression Detection
Guangdong-Hong Kong-Macao Joint Laboratory of Human-Machine Intelligence-Synergy Systems, Shenzhen Institutes of Advanced Technology, Chinese Academy of Sciences（中国科学院深圳先进技术研究院粤港澳人机协同智能系统联合实验室）；University of Chinese Academy of Sciences（中国科学院大学）；Good Mood Health Industry Group Co., Ltd（好心情健康产业集团有限公司）；Shanghai Jiao Tong University（上海交通大学）
DAIC-WOZ: On the Validity of Using the Therapist's prompts in Automatic Depression Detection from Clinical Interviews
Idiap Research Institute（伊迪亚普研究所）；Mathematics Research Center (CIMAT)（数学研究中心（CIMAT））；Consejo Nacional de Humanidades, Ciencias y Tecnologías (CONAHCYT)（国家人文科学与技术委员会（CONAHCYT））；Brno University of Technology（布尔诺理工大学）
UPLME: Uncertainty-Aware Probabilistic Language Modelling for Robust Empathy Regression
School of Electrical Engineering, Computing and Mathematical Sciences, Curtin University（电气工程、计算与数学科学学院，科廷大学）；North South University（北南大学）；BRAC University（布拉克大学）；The Australian National University（澳大利亚国立大学）；University of ÓBuda（奥布达大学）
