True Audio Restoration for Music:
Restore Signal, Not Noise.
Reconstruct missing audio information removed by lossy codecs in music thanks to generative neural networks
Upload an audio file
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How It Works
Import Audio
Upload music or enter the link to a AI-generated track (SUNO, Udio, Producer.ai...)
Neural Reconstruction
The model predicts the most likely high-resolution signal that could have produced the audio.
Download WAV
Export a restored 24-bit WAV with reduced artifacts and improved temporal detail.
Examples of restored AI generated music
Most music generation AI models are trained on low quality audio files, so they generate low quality audio.
Use Neural Analog to restore the frequencies from AI generated music or from stems.
Example: stem of a mp3 music generated with Demucs
Example: Classical music generated with SUNO
How does the Restoration model work?
Learned Signal Statistics
The model is trained on pairs of clean, high-resolution audio and their degraded counterparts. It learns the statistical structure of real harmonic content, transients, and phase.
Time-Domain Consistency
Reconstruction is constrained in the time domain. Added detail must remain phase-coherent and temporally stable.
Objective Quality Metrics
Outputs are optimized against perceptual and signal-based metrics. The result? Clearer high ends, less wobbles, and larger sound.
Frequently Asked Questions
Methodology Comparison Table
| Feature | Interpolation | Mastering (EQ/Comp) | Neural Analog |
|---|---|---|---|
| Method | Mathematical curve fitting | Frequency/Dynamic adjustment | Generative AI Reconstruction |
| Bandwidth Extension | Yes (Restored) | ||
| Artifact Removal | (Often worse) | Yes (De-quantization) | |
| Bit Depth | Padded zeros | 16/24-bit | True 24-bit |
| Process | Upsampling | Polishing | Restoration |
Don't settle for subpar audio quality.
Restore your audio files today and improve your audience's experience.
Import Your First Track