I've been loving the app. The audio restoration works amazing on my suno songs
True Audio Restoration:
Restore Signal, Not Noise.
Reconstruct missing audio information removed by lossy codecs in music with Generative Neural Networks.
SELECT RESTORATION TYPE
Or
Upload audio files
Drag & drop or click to browse (multiple files supported)
Supports: MP3, MPEG, MP2, MPGA, WAV, WAV, AIFF, AIF, AIFF, AIF, FLAC, AAC, OGG, OPUS, M4A, MP4, WEBM, WMA, ALAC, AMRMax size: 50MB.
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 high quality WAV with reduced artifacts and improved temporal detail.
See Neural Analog in Action
Restore missing high frequencies
Low sample rate musics, such as old recordings or AI generated tracks, miss high frequencies. This example uses AudioSR with a 4kHz cutoff in mono.
Example: AudioSR restoration (4kHz cutoff, mono)
Remove clipping from poor recordings
Clipping happens when audio is too loud to be encoded. Use Neural Analog to remove clipping artifacts while maintaining high volume.
Example: Remove Clipping + DACVAE upscaling on old mp3 file
Upscale English speech and improve audio quality
Use Neural Analog to upscale voice tracks, singing, and speech thanks to the NovaSR model.
Example: Upscaled speech with NovaSR (mono)
Remove background noise and restore voice tone
Use stem splitting to separate vocals from background noise, the NovaSR upscaling model to generate missing frequencies, and Match EQ to restore natural tonal balance.
Example: Voice notes with heavy distorsion, phone recording, and background noise
Trusted by 14,000+ music lovers
Neural Analog makes me feel like a monkey with an AK-47, in the best way possible
It worked! Well done :) Many thanks :))))
Wow thank you so much i upscale videos and take out live recordings from music because of my autism i hate the crowd
Amazing tool for audio. Clean, simple, and effective. I would spend hours in RX to get the same results. Give it a try. I can save you hours of production time.
H
Hasina
4 out of 5 stars
Useful app besides AudioSR that needs improvement for AI vocals high frequencies restoration. It sometimes adds a straight line at 10kHz or reduces the 5-10kHz volume. I only got the right correction on my 5th restoration of the same vocal.
TG
The Grim Tower
5 out of 5 stars
Love it! Makes everything crisp!
SH
Shrunken Head
5 out of 5 stars
IT'S GREAT
F
Francisco
5 out of 5 stars
Sensacional
TS
Tommi, Studionet
5 out of 5 stars
Highend services!
Listen to tracks made by our users
AI audio enhanced with Neural Analog
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
Yes. Humans hear frequencies between 20 Hz to 20 kHz. Low quality audio hardware, like smartphones, can easily play these frequencies.
Unfortunately, hearing degrades with age and with exposure to loud sounds. For example, the famous ultrasound "Mosquitone" (17.8kHz) is clearly audible to younger people, but notoriously difficult to hear for adults.
However, even if not directly heard, high-frequency content is crucial for the transient response and "spatial feel" of audio, which impacts how you perceive quality even if you don't consciously hear a sine wave at that pitch.
Simple WAV conversion does not add missing detail. Conversion in tools like Audacity mostly repackages existing samples through interpolation, while True Audio Restoration uses generative AI (similar to image super-resolution) to predict and insert missing detail, recovering dynamic range and "air" lost to compression.
Restoration and mastering solve different problems. Many mastering services rely on multiband compression to boost or compress existing frequencies, so mastering without restoration can amplify artifacts instead of fixing the root quality issue.
Once your audio is restored, Automatic Mastering can polish it for professional release, with intelligent loudness optimization tailored to your track.
Audio restoration analyzes spectral content and removes lossy-compression "chirps" and "warbles", replacing them with coherent harmonic content.
That's okay! Restoration is not a silver bullet. Neural Analog offers other tools such as stem splitting and mastering to power your music creation. This enables a hybrid production workflow where you can replace low-quality AI elements entirely.
No, it does not just add noise. Unlike enhancers that layer white noise, the generative model reconstructs the clean signal that should be there by separating useful harmonic and transient structure from compression artifacts and other degradations.
You can restore audio for free on a sample. For longer audio, restoration uses processing minutes. Your free weekly processing minutes are used first, then any purchased processing minutes.
Yes, it can work on old codecs and low bit-depth audio. Processing is based on raw signal rather than a specific codec, so trying a sample is the best way to evaluate performance.
Yes. Support depends on the model. UniverSR, AudioSR, and FlashSR upscale low resolution audio to 48 kHz (super resolution). The 'Music Upscaler' restoration algorithm keeps 48 kHz sources at 48 kHz, and restores 44.1Khz-or-lower sources at 44.1Khz.
Yes, you can run restoration more than once. You can change the selected Source to run another pass on already restored audio, and batch imports support an 'Iterative restoration' toggle that selects the latest restored version of each file.
A single restoration model may not fix every problem. If the track sounds flat or weak in the low end, try a stem-based workflow:
- Split the song using the 4-stem preset.
- Select the bass stem.
- Enhance it with Neural Remix.
- Use EQ to boost or clean the low end if needed.
- Blend the processed version with the original if the result is too strong.
UniverSR is better for missing high frequencies. Neural Remix and EQ are often better starting points for bass, muddiness, or low-end problems.
Some restoration changes happen mostly in very high frequencies, so they may be subtle depending on your hearing, speakers, headphones, and the source file.
You can compare the spectrogram to see what changed. If the source already has enough high-frequency content, or if the problem is mostly bass, arrangement, mixing, or artifacts in the voice, a different tool may be more useful.
Try stem splitting, Neural Remix, EQ, Match EQ, or mastering depending on what you want to fix.
Don't settle for subpar audio quality.
Restore your audio files today and improve your audience's experience.