The AIRSONG project aims to advance scientific understanding and computational modeling of respiratory entrainment, with applications in biofeedback to promote relaxation and well-being. The project leverages dynamical systems theory to investigate how coupled oscillator models can describe and optimize human-auditory synchronization to encourage healthier breathing patterns and enhance physiological and psychological outcomes. The project focuses on three objectives: to deepen understanding of respiratory entrainment and its role in reducing stress, design intuitive sonification strategies to guide breathing patterns effectively, and develop advanced coupled oscillator models that capture and optimize the complex dynamics of respiratory and cardiac entrainment. To achieve these objectives, the research employs non-linear analysis of respiratory-cardiac interactions to design and refine adaptive algorithms that respond dynamically to individual differences. Empirical studies will evaluate the impact of adaptive auditory feedback on breathing patterns, heart rate variability, and relaxation in both individual and collective contexts, providing insights into the potential of biofeedback interventions. Integrating the disciplines of psychophysiology, computational modeling, human-computer interaction, and music cognition, AIRSONG aims to advance the understanding of physiological synchronization, paving the way for more effective biofeedback systems that promote well-being.