Preliminary Study of AI-Based Personalized Music Intervention for Alleviating Anxiety and Depression
This project explores the feasibility of using artificial intelligence to generate personalized music interventions aimed at reducing mental distress, such as anxiety and depression. The objective is to develop and evaluate an AI-driven music generation model tailored to the psychological needs of individual subjects. We will collaborate with the UTSA Psychology Department to recruit participants and assess the effectiveness of personalized AI-generated music in reducing mental health symptoms. The key areas of focus include AI model development, music personalization algorithms, and psychological impact assessment.
- Faculty: Chen Pan
- Department: Electrical and Computer Engineering
- Open Positions: 3
- Mode: On-Campus (In-person)
- Hours per week: 15
Requirements and Responsibilities:
Needed Skills: Students should possess basic programming skills, preferably in Python. Familiarity with machine learning concepts and experience with tools like TensorFlow or PyTorch is beneficial but not required. Knowledge of digital signal processing (DSP) is essential, and a background in music theory or psychology is advantageous.
Student Responsibilities:
- Assist in the development and testing of AI models for music generation.
- Collaborate in designing and conducting experiments, including data collection from subjects.
- Analyze collected data and support the interpretation of research findings.
- Engage in interdisciplinary collaboration with the psychology department.
- Prepare research materials and contribute to documentation and dissemination of the results.
