Personalized music therapy information system based on algorithmic composition in the treatment of Autism Spectrum Disorder.

Abstract

We utilize information technology, especially artificial intelligence algorithms and computer music techniques, to enhance the emotional understanding abilities of children with autism. The proposed information system includes a machine composition engine, a music therapy app, and a music database for coping with autism. First, we will develop a machine composition engine to provide the effective, economic, and personalized music therapy for autistic children. Music therapy has been validated as helpful for autism, and it is very suitable for children with limitations in physical activity and functional fitness. The music generated explicitly for recognizing and understanding certain emotions will have a much better curative effect by considering the preference and the situation of individuals. In addition, the usage of artificial intelligence will largely reduce the cost and time of music composition. Second, we plan to develop a musical therapy app that is child friendly. We will consider the special needs of the children, such as the size of the font, in mobile application design. It will provide a joyful and engaging way for children to relieve autism and benefit their psychological well-being and quality of life. Finally, we will build a large-scale music database for the free usage of the public and promote our service to the world. The research will provide an effective, low-cost, and personalized music therapy information system that directly benefits children with autism and their families by improving their emotional understanding, and informing the development of upcoming products and services, especially artificial intelligence technology.