Sounding emotions: an integrative review on ai-generated music and expressive lyric writing to support students with verbal expression challenges - Zandra, Rully Aprilia; Setiyowati, Arbin Janu; Hidayatullah, Hengki Tri (Universitas Ahmad Dahlan, 2025)
This integrative review investigates the potential of expressive lyric writing and AI-generated music as alternative, non-verbal modalities to support emotional articulation and well-being among students—particularly in secondary school and counseling program settings—who face challenges in verbal expression. Students with limited verbal communication skills often struggle to articulate their emotional experiences through conventional language-based approaches, leaving them vulnerable to emotional suppression and psychological distress. Drawing from a systematic synthesis of 18 peer-reviewed articles published between 2011 and 2025, this review integrates findings across diverse methodologies (qualitative, experimental, computational, and mixed-methods) and geographic contexts. Two thematic clusters emerged: (1) expressive lyrics as a medium of emotional catharsis and identity construction, and (2) music—particularly instrumental, adaptive, and AI-generated—as a channel for affective resonance and personalized emotional support. The findings suggest that lyrics and music not only serve as creative outlets but also function as therapeutic tools that bridge emotional expression and psychological reflection. Building on this synthesis, the review proposes an integrative model that guides students from emotion-based lyric writing to AI-facilitated musical interpretation, culminating in counselor-guided interventions. This model offers a structured yet flexible approach to enhancing emotional literacy and engagement for students with communicative limitations. The review concludes by calling for further empirical testing of the model and deeper integration of expressive arts and intelligent technologies into school-based counseling and mental health programs.