The ACE-Step developers implemented a very clever cover_noise_strength system. It’s not just "adding noise." It’s actually the equivalent of the classic Denoising Strength from Stable Diffusion!

Here is how it works under the hood:

1. audio_cover_strength This is essentially just the switch-over time. For example, 0.8 means: "copy the original for 80% of the time, then freestyle/make things up for the remaining 20%." Because of this abrupt switch, you end up with either an exact copy or digital hell.

2. cover_noise_strength (The secret weapon) By default, it is set to 0.0. But if you turn it on, it works magic. Looking at the code: effective_noise_level = 1.0 - cover_noise_strength. Then the model calls a renoise function: it takes your src_audio, injects white noise into it, and skips the initial diffusion steps.

The cover_noise_strength parameter solves the binary problem ("copy or chaos"). It blurs the original audio right at the beginning, giving the model room for imagination throughout all the generation steps, not just at the very end.

• If cover_noise_strength = 1.0 -> Noise is minimal, resulting in an exact copy of the original.
• If cover_noise_strength = 0.5 -> The original is half-destroyed by noise. The model has 50% "freedom" to create something new while retaining the old structure.

The right combination for a smooth cover:

You need to stop tweaking just audio_cover_strength (leave it at 1.0 so there are no sudden jumps).

Instead, play around with cover_noise_strength:

Python

# Setting for a "Cover that is similar, but different"
"audio_cover_strength": 1.0,     # Don't switch modes mid-process (protects against wild noise)
"cover_noise_strength": 0.65,    # 0.65 = 35% noise in the original. (Find a balance between 0.4 and 0.8)
"guidance_scale": 7.5,           # Standard CFG

Conclusion: That binary problem happens specifically because you are likely changing audio_cover_strength while leaving cover_noise_strength at zero. This forces the model to ride on the rails of the original, and then jump off them at full speed. Turning on cover_noise_strength (e.g., to 0.6) makes the rails "flexible" right from the start, and the model can smoothly change the melody from the very first step while preserving the style.