Affective Computing-Based Adaptive Music Generation for Human–Animal Assisted Wellness
Keywords:
affective computing; adaptive music generation; human–animal interaction; wellness infrastructure; algorithmic governanceAbstract
The integration of affective computing with generative music systems offers new possibilities for adaptive wellness interventions, yet the extension of these systems to human–animal assisted settings remains underexplored. This paper presents a system-level analysis of affective computing-based adaptive music generation for human–animal assisted wellness. The discussion focuses on architectural organization, multimodal sensing, animal state inference, generative music control, interaction dynamics, robustness, fairness, governance, and sustainable deployment. Rather than proposing a single algorithmic solution, the paper argues that human–animal musical co-regulation should be understood as a multi-agent socio-technical infrastructure. A layered architecture is examined in which sensing, state modeling, music generation, and intervention policy operate through separate but coordinated planes. This separation supports oversight, modular evolution, and graceful degradation under real-world constraints. The paper highlights the asymmetries between human and animal participants, particularly the absence of direct animal self-report and the resulting dependence on behavioral and physiological inference. Evaluation is discussed as a pluralistic process requiring multiple weak labels and contextual interpretation. Fairness is considered across both human demographic differences and animal phenotypic or species-specific variation. Governance implications are analyzed through frameworks of accountability, transparency, and animal welfare, emphasizing that animal well-being should function as a hard constraint rather than a secondary objective. Deployment challenges related to edge computing, model sustainability, privacy, and operational usability are also examined. The paper concludes that trustworthy human–animal adaptive music systems require deep integration of technical design with ethical and infrastructural reasoning, and that future progress depends on longitudinal, cross-disciplinary, and species-inclusive research.
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This article is published under the Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
