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Generative models that apply denoising diffusion processes specifically to audio signals and musical tracks.
Distinct from Diffusion Models: Focuses on audio synthesis rather than the image synthesis standard defined in the parent Diffusion Models tag.
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ACE-Step is a high-fidelity audio synthesis system and diffusion model designed to generate music and vocals from text descriptions. It functions as a music generator and vocal synthesizer, using a diffusion transformer decoder to produce audio across various languages and genres. The project provides tools for text-guided audio editing, including the ability to extend the duration of tracks, regenerate specific song segments, and perform latent-space audio inpainting to modify lyrics or styles. It also includes a framework for audio style fine-tuning using low-rank adaptation to adapt vocal
Implements a diffusion transformer decoder for generating and editing musical tracks and vocal samples.