Music Therapy for Autism Spectrum Disorder: A Comprehensive Literature Review on Therapeutic Efficacy, Limitations, and AI Integration

Autism Spectrum Disorder (ASD) is a neurological and developmental condition that presents considerable social, behavioral, and communicative challenges to those diagnosed with it. Recent advances in music therapy have shown promising results in addressing these challenges. This review examines studies on music therapy for ASD from 2020 to 2024, covering both biomedical and interdisciplinary repositories. Our analysis reveals that music therapy can effectively enhance communication and social skills in people with ASD. Based on the results from 18 selected studies, the most significant improvements are achieved in social-emotional reciprocity and adaptive behaviors, contrasting with only modest improvements in social relationship deficits. Among the intervention approaches assessed, improvising and playing an instrument achieved slightly better outcomes. However, while promising, the robustness of such conclusions is bound by small sample sizes, insufficient longitudinal studies, and limited age diversity among participants. These limitations underscore the need for largerscale, more diverse, and more in-depth research to confirm the findings and extend their generalizability. Previous reviews have discussed the application of technologies such as robots, virtual reality (VR), and wearable devices in music therapy for ASD. This review expands on these discussions by exploring the integration of artificial intelligence (AI), which offers significant potential to enhance the personalization, adaptiveness, and efficacy of traditional music interventions for ASD. We explore promising avenues for multifaceted AI applications in music selection and generation, and automatic emotion and response detection, while also discussing the challenges of implementing AI in music therapy for ASD.