Is This Song AI Generated?
Upload the track and find out how strongly the audio itself leans that way.
It is the question every listener now asks about unfamiliar music, and it deserves a better answer than a confident yes or no. This page gives you two things: a free detector that measures the recording, and an honest account of how much weight that measurement can carry.
The detector runs entirely in your browser. Nothing is uploaded, no account is needed, and the result comes with its own reasoning attached.
Upload Audio or Drag & Drop
Upload an audio file to receive a probabilistic analysis of characteristics associated with AI-generated music.
- MP3
- WAV
- M4A
- FLAC
- OGG
- AAC
- WebM
MP3, WAV, FLAC, AAC, M4A, OGG, WebM · max 25 MB · min 10 seconds · 30+ seconds recommended
Your audio never leaves your device. Decoding and analysis run entirely in this browser tab, and nothing is uploaded to a server. Your audio is processed only to perform this analysis, and your uploaded audio and temporary analysis data are automatically deleted after processing. No report links are created, and your analysis is never publicly accessible. Upload only audio you are authorised to process — analysis does not transfer ownership or publishing rights.
- Free
- Fast
- Secure
- No registration
How to answer the question responsibly
Think of it as three independent lines of evidence, weighted in this order. Provenance is the strongest: project files, stems, dated drafts, a coherent back catalogue, and a straightforward explanation from the artist. Context is second: how the track appeared, who uploaded it, how quickly, alongside how much other material, and whether the release pattern is plausible for a human working at that pace.
Acoustic analysis is third. It is the only one you can run yourself in thirty seconds, which is exactly why it gets over-weighted. Use it to raise or lower your suspicion, not to settle the matter.
- Provenance: session files, stems, drafts, release history — strongest
- Context: upload pattern, volume of output, account age — moderate
- Acoustic analysis: what this detector measures — supporting evidence only
- Vibes: how the track 'feels' — the weakest and most bias-prone signal of all
What this tool measures
Your browser samples up to five sections of the track and runs a Hann-windowed FFT over each. From that it derives the spectral ceiling, cross-segment tonal agreement, crest factor, spectral-centroid variability, high-band energy ratio and stereo correlation.
Those measurements are weighted, combined and deliberately shrunk toward the middle, then capped between 15% and 85% because the underlying analysis engine has not yet been calibrated against a labelled dataset. When sampled sections disagree, or the file is too degraded, the tool returns Inconclusive rather than guessing.
Why the answer is often wrong in both directions
Human music produces false positives routinely. Loudness-maximised electronic tracks, template-driven pop, tightly quantised programming and low-bitrate uploads all reproduce the same measurable signature as much generated audio.
Generated music produces false negatives just as routinely. Newer models leave fewer artefacts, and any human post-production — re-recording, re-mixing, adding a live instrument, running the file through analogue gear — removes most of what remains.
This is not a flaw in one tool. It is the current state of the entire field, and any product that hides it from you is selling confidence rather than information.
Before you accuse anyone
AI-assisted and AI-generated music is legal. Plenty of musicians use generative tools openly and say so. A detector score is not grounds for a takedown, a failing grade, a disciplinary process, a contract termination or a public callout — and this result is explicitly not forensic evidence.
If the question genuinely matters, ask the artist for the project files. That single request resolves more cases than any acoustic tool ever will.
Frequently asked questions
Not with certainty, and you should distrust anything that claims otherwise. What a tool can do is measure the recording and report how strongly its properties resemble patterns common in generated audio. That is a probability, and it belongs alongside provenance evidence rather than replacing it.