discrete diffusion model conditioned on textual CLIP embeddings for the generation part [Radford
et al., 2021]. Kreuk et al. [2022] proposed applying a transformer language model over discrete audio
representation, obtained by quantizing directly time-domain signals using EnCodec [Défossez et al.,
2022]. Sheffer and Adi [2023] followed a similar approach to Kreuk et al. [2022] for image-to-audio
generation. Huang et al. [2023a], Liu et al. [2023] proposed using latent diffusion models for the task
of text-to-audio, while extending it to various other tasks such as inpainting, image-to-audio, etc.
Simple and Controllable Music Generation