IEEE Transactions on Affective Computing, 2020 /TAC2020/

• Depression Level Prediction Using Deep Spatiotemporal Features and Multilayer Bi-LTSM
• Ordinal Logistic Regression With Partial Proportional Odds for Depression Prediction

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IEEE Transactions on Affective Computing, 2022 /TAC2022/

• Prediction of Depression Severity Based on the Prosodic and Semantic Features With Bidirectional LSTM and Time Distributed CNN
• Dual Attention and Element Recalibration Networks for Automatic Depression Level Prediction

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2022 IEEE 11th Global Conference on Consumer Electronics (GCCE). IEEE, 2022 /TAC2022/

• A Transformer-based Multimodal Network for Audiovisual Depression Prediction

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ICASSP 2020-2020 IEEE international conference on acoustics, speech and signal processing (ICASSP). IEEE /ICASSP2020/

• HIERARCHICAL ATTENTION TRANSFER NETWORKS FOR DEPRESSION ASSESSMENT FROM SPEECH

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ICASSP 2021-2021 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP). IEEE /ICASSP2021/

• MULTI-SCALE AND MULTI-REGION FACIAL DISCRIMINATIVE REPRESENTATION FOR AUTOMATIC DEPRESSION LEVEL PREDI

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Proceedings of the 2022 International Conference on Multimodal Interaction. 2022. /ICML22/

• Text-based Interpretable Depression Severity Modeling via Symptom Predictions

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IEEE Journal of Biomedical and Health Informatics, 2023. /J-BHI23_一区TOP/

• Trustworthy Data and AI Environments for Clinical Prediction: Application to Crisis-Risk in People With Depression

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Procedia Computer Science, 2020，会议论文专刊

• An End-to-End Model for Detection and Assessment of Depression Levels using Speech 

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2023 IEEE International Instrumentation and Measurement Technology Conference (I2MTC). IEEE, 2023

• Development of Sorrow Analysis Dataset for Speech Depression Prediction