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A First Look at Generative Artificial Intelligence Based Music Therapy for Mental Disorders

MCML Authors

Björn Schuller

Prof. Dr.

Principal Investigator

Health Informatics

Abstract

Mental disorders show a rapid increase and cause considerable harm to individuals as well as the society in recent decade. Hence, mental disorders have become a serious public health challenge in nowadays society. Timely treatment of mental disorders plays a critical role for reducing the harm of mental illness to individuals and society. Music therapy is a type of non-pharmaceutical method in treating such mental disorders. However, conventional music therapy suffers from a number of issues resulting in a lack of popularity. Thanks to the rapid development of Artificial Intelligence (AI), especially the AI Generated Content (AIGC), it provides a chance to address these issues. Nevertheless, to the best of our knowledge, there is no work investigating music therapy from AIGC and closed-loop perspective. In this paper, we summarise some universal music therapy methods and discuss their shortages. Then, we indicate some AIGC techniques, especially the music generation, for their application in music therapy. Moreover, we present a closed-loop music therapy system and introduce its implementation details. Finally, we discuss some challenges in AIGC-based music therapy with proposing further research direction, and we suggest the potential of this system to become a consumer-grade product for treating mental disorders.

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