Audio SR (48 kHz Upscale) 🔊

If you've generated audio - LTX-2 dialogue, AceStep music, anything coming out of a video model - you know the sound: it dies around 11–12 kHz. Not "quiet up top," gone. Audio SR is bandwidth extension, and this node wraps the real AudioSR latent-diffusion model to fix exactly that. It doesn't filter or fake the high end; it invents plausible 11–24 kHz content from the structure it can hear. The measured result on a real take is wild: transparent below about 12 kHz, then +30 dB at 16–20 kHz and +56 dB at 20–24 kHz. The octave above the roll-off is written from nothing, which is precisely the job.

This is genuinely a thing people do, not a toy. A widely-shared r/StableDiffusion post pushed AudioSR as a post-processing step for LTX-2's audio - "upscales" the audio "sort of like how SeedVR2 does for images," in the commenter's words - and the same model backs this node. Community consensus there was that the audiosr_basic checkpoint beat the speech one even for voice, but the node's own docs say the variant is read from the filename, so keep the shipped names and A/B if you care.

The model is vendored inside the pack (audio_sr/vendor/audiosr, MIT), so you don't need a second pack installed - but you do need a checkpoint, dropped into ComfyUI/models/AudioSR. The fp32 files run about 6 GB each; dtype gives you fp16/bf16 if VRAM says otherwise. That 6 GB is also what keep_loaded (on by default) holds in VRAM between runs - flip it off to free the card after each run and pay the load time again.

Inputs worth your attention:

• steps - DDIM steps per chunk, and the whole cost: total work is chunks × steps. 50 is the sane default here; upstream's own default is 200, four times the wait for a difference you'll struggle to hear on a mix.
• stereo - AudioSR is a mono model. mid/side (keep the image) is the recommended mode: only the mid channel goes through the model, side is carried through untouched, so a stereo image survives. sum to mono is what the old wrapper did, and it was measured to flatten an L/R correlation of +0.45 and a side/mid RMS of 0.61 to 1.00 and 0.00 - the whole image, gone.
• chunk_seconds / overlap_seconds - chunking with a Hann crossfade (which sums to 1, so joins neither dip nor double). 1 s of overlap is cheap insurance; the default 15.36 s is 3 × 5.12 s because the batch builder pads every chunk up to a multiple of 5.12 s - pay for silence otherwise.
• seed - worth holding fixed while you compare steps or chunk lengths, or you're comparing two different inventions of the high end. Capped at 2³²−1 because AudioSR's seed_everything() calls numpy, which refuses anything bigger.

Outputs are audio (48 kHz mono, or mid/side-recombined stereo) and report - a text summary of what was actually done, always available on the output even if you turn verbose off.

Installing

Part of Kinburg-Nodes: ComfyUI Manager → search "Kinburg-Nodes", or git clone https://github.com/Kinburg/Kinburg-Nodes into custom_nodes, then restart. On top of the pack, download an AudioSR checkpoint into ComfyUI/models/AudioSR. The vendored model code ships with the pack, so no pip install beyond what Manager already runs.

Gotchas

Never run L and R separately: two independent diffusion passes decorrelate and the invented top comes out phasey instead of wide. Upscale before you widen, not after. And don't mistake match_level for a loudness match - it puts the energy below 10 kHz back where the input's was, because the model genuinely adds energy up top and matching totals would turn the whole track down to pay for it. It fixes dead top end; it won't fix aliasing artifacts baked into the source. Nothing will.