Output Music Samples

This study presents a comprehensive framework for a real-time, context-sensitive neural audio generation system that dynamically aligns its output with human brainwave patterns. By integrating deep learning techniques with frequency modulation strategies, the system successfully adapts musical content to suit specific cognitive and emotional states such as sleep, focus, relaxation, meditation, and energy stimulation. The architecture combines convolutional neural networks with contextual conditioning, allowing for fine-grained modulation of latent audio features in a neurologically informed manner.