Example Concept: Diffusion-based audio models generate singing vocals by starting with a noisy audio signal and gradually refining it through multiple iterations. Each iteration applies learned patterns from a training dataset, which includes various singing styles and vocal characteristics. This process allows the model to synthesize vocals that sound natural and expressive, capturing nuances like pitch, timbre, and dynamics.