Sampling in hip hop is about taking 1 or 2 audio sources mapping them into some new audio, SD was trained on 2.3 billion data points. In a diffusion model you put noise on an input image, until its recognizeable. For a song this would mean, making it unrecognizable by making it literally sound like noise, and then try to denoise it, this process wouldn't be very helpful i assume, but might be a good experiment. Open AI's Jukebox uses an autoenconder method with autoregressive transformers, given this architecture, i would assume you can theoretically do stable diffusion architecture on audio, to generate new audio. https://openai.com/blog/jukebox/