README.md

metadata

title: Synth Cue Restoration Studio
emoji: 🎛️
colorFrom: purple
colorTo: blue
sdk: gradio
sdk_version: 6.19.0
app_file: app.py
pinned: false

Synth Cue Restoration Studio

A Gradio tool for restoring degraded analog-synth score cues transferred from flawed master tapes. Upload a degraded audio file and, optionally, a clean reference clip to guide tonal (EQ) matching.

What it does

• Noise reduction — spectral-gating denoise for tape hiss / transfer noise
• Declick / dropout repair — detects and interpolates across impulsive clicks, pops, and short dropouts, using a local (not global) threshold so it doesn't fire on dense musical passages
• Wow & flutter smoothing — gently corrects slow pitch/speed drift from tape stretch or warp
• High-frequency restoration — a harmonic exciter that regenerates plausible top-end lost to bandwidth-limited transfers
• Reference spectral + stereo-width matching — provide a clean reference clip and the tool measures its tonal balance and stereo width live, then nudges your restored cue toward those measured values

This is a general-purpose DSP restoration pipeline. It processes whatever audio you upload — it does not generate or reproduce any copyrighted composition on its own.

Important: always use a matching reference, not a generic one

Analysis across multiple clean cues from this score showed no single consistent "target" tone — stereo width ranges from near-mono to very wide/decorrelated, and brightness ranges from ~6kHz to ~17.6kHz rolloff depending on the specific cue. There is no universal profile to aim for. Always upload the clean counterpart of the exact cue you're restoring, not an unrelated reference clip, or the spectral/width matching will nudge the audio toward the wrong target.

Presets

Three one-click presets seed the sliders based on measured degradation patterns, not tonal target:

• Broadband Noise Cue — bandwidth already close to intact relative to its own reference, main issue is hiss
• Bandwidth-Limited Cue — real high-frequency loss and a narrower stereo image relative to its own reference
• Heavy Click / Worn Duplication — click rate several times higher than typical, often with reduced dynamic range

Running locally

pip install -r requirements.txt
python app.py

Deploying to Hugging Face Spaces

1. Create a new Space at huggingface.co/new-space, SDK = Gradio.
2. Copy app.py, requirements.txt, and this README.md into the repo (or git clone the Space repo and drop these files in).
3. git add . && git commit -m "Initial restoration studio" && git push
4. The Space will build automatically and give you a live URL.