6 papers
Learning to Attend to Depression-Related Patterns: An Adaptive Cross-Modal Gating Network for Depression Detection
Hangbin Yu, Yudong Yang, Rongfeng Su +2
Automatic depression detection using speech signals with acoustic and textual modalities is a promising approach for early diagnosis. Depression-related patterns exhibit sparsity i…
From Speech to Profile: A Protocol-Driven LLM Agent for Psychological Profile Generation
Xingjian Yang, Yudong Yang, Zhixing Guo +3
The psychological profile that structurally documents the case of a depression patient is essential for psychotherapy. Large language models can be applied to summarize the profile…
UTI-LLM: A Personalized Articulatory-Speech Therapy Assistance System Based on Multimodal Large Language Model
Yudong Yang, Xiaokang Liu, Shaofeng zhao +3
Speech therapy is essential for rehabilitating speech disorders caused by neurological impairments such as stroke. However, traditional manual and computer-assisted systems are lim…
Magnitude and Phase-based Feature Fusion Using Co-attention Mechanism for Speaker recognition
Rongfeng Su, Mengjie Du, Xiaokang Liu +2
Phase-based features related to vocal source characteristics can be incorporated into magnitude-based speaker recognition systems to improve the system performance. However, tradit…
Investigating Acoustic-Textual Emotional Inconsistency Information for Automatic Depression Detection
Rongfeng Su, Changqing Xu, Xinyi Wu +4
Previous studies have demonstrated that emotional features from a single acoustic sentiment label can enhance depression diagnosis accuracy. Additionally, according to the Emotion…
Structured Dialogue System for Mental Health: An LLM Chatbot Leveraging the PM+ Guidelines
Yixiang Chen, Xinyu Zhang, Jinran Wang +4
The Structured Dialogue System, referred to as SuDoSys, is an innovative Large Language Model (LLM)-based chatbot designed to provide psychological counseling. SuDoSys leverages th…