Questions, answered straight
25 questions people actually ask about AI music detection, each answered in a single short paragraph you can quote. Every answer states what is measurable, what is not, and where the estimate breaks. No accuracy figure appears anywhere on this site until it has been measured.
Last updated August 2026 · engine build ensemble-1
Can AI-generated music actually be detected?
Can AI-generated music be detected?
Sometimes, but not with certainty from audio alone. Detectors measure patterns that correlate with generated audio — spectral behaviour, stereo structure, timing regularity, transient shape. Compression, mastering, genre, generator updates and human post-production all move those signals. Treat any result as probabilistic evidence about a recording, never as proof of who or what made it.
Is there a free tool to check if a song is AI generated?
Yes. AI Music Detector is free, requires no account, and analyses the file in your browser, so the audio is never uploaded to a server. You drop in an audio file, the engine measures it locally, and you get a probability, a confidence level and the measurements behind both. There is no paid tier withholding the result.
What does an AI music detector actually measure?
Not meaning or style. This engine measures signal properties: energy distribution across frequency, the presence and shape of a high-frequency ceiling, stereo correlation and width, dynamic range and loudness behaviour, transient sharpness, timing regularity, and repeated spectral texture across sections. Four independent models score those measurements and a weighted vote combines them.
Do AI music detectors upload my file?
Many do; this one does not. Analysis runs entirely in your browser using the Web Audio API, so the recording never leaves your device and no copy is stored. You can verify it: open your browser's network panel, run an analysis, and confirm no request carries your audio. The result is discarded when you leave the page.
How accurate is AI music detection?
How accurate are AI music detectors?
Nobody publishing a single headline percentage can support it. Accuracy depends on the generator, its version, the encode, the genre and how much human production followed. We publish a benchmark protocol with per-generator and per-encode arms rather than one number, and the result cells stay empty until they are measured rather than estimated.
Should I trust a detector that claims 99% accuracy?
No, not without the disclosures behind it. A usable claim states the corpus size and composition, the generators and versions tested, the false-positive rate on verified human music, the encode conditions, the abstention rate, and the build that produced the figure. A bare percentage with none of that is marketing, not measurement.
Why did a detector say my own song is AI generated?
The most common causes are heavy limiting, a lossy source file, tightly quantised programming, dense in-the-box production with stock instruments, and short clips. All of those push a human recording toward the same measurements generated audio tends to show. A high score is a statement about the signal, not an accusation about you.
Does MP3 compression affect AI detection?
Substantially, and it is the single largest error source here. Several measurements live in the frequency band an encoder discards first, so a low-bitrate MP3 of an acoustic session can show the same hard spectral ceiling as generated audio. Always analyse the highest-quality version you have, ideally WAV or FLAC.
Do detectors flag electronic music as AI?
It is the hardest human case. Fully synthetic, quantised, heavily processed human-authored electronic music shares many measurable properties with generated audio: narrow dynamics, exact timing, synthetic timbres. The engine cannot separate authorship from production style, so it lowers confidence rather than pretending to. Read electronic-genre results with extra scepticism.
What does “inconclusive” mean in a result?
It means the evidence sits too close to the decision boundary, the models disagreed with each other, or the source quality removed detail the analysis needs. Rather than round an unreliable reading into a verdict, the engine abstains and says so. An inconclusive result is information about the file's analysability, not a hidden yes.
What is the difference between probability and confidence?
Probability answers “how much does this recording resemble AI-generated audio?” Confidence answers “how reliable is that estimate?” They move independently. A 72% probability at low confidence — short clip, lossy source, disagreeing models — is much weaker evidence than 62% at high confidence. Always read the pair, never the headline number alone.
Suno, Udio and other generators
Can a detector tell which generator made a track?
This one cannot, and treats claims that it can with suspicion. There is no per-generator classifier in the engine; when evidence leans generated, the report says “unknown AI generator” and stops. Attribution would require labelled training data for every model version, and generator releases move faster than any such dataset.
How do I tell if a song was made with Suno?
You can look for the cues Suno output commonly shows — a consistent high-frequency ceiling, smoothed transients, section-level repetition of spectral texture, vocal consonants that stay uniformly clean — but none of those identify the tool. Metadata, upload history and the uploader's own account of the process are stronger evidence than any audio measurement.
Which generators are hardest to detect?
Whichever shipped most recently. Each release narrows the measurable gap, and the newest versions tend to fix exactly the artefacts that older detectors relied on. Tracks that were rendered from a generator and then re-produced by a human — re-mixed, re-mastered, partly re-recorded — are harder still, because the human stage overwrites the evidence.
Are hybrid human/AI tracks detectable?
Not as a clean answer, because there isn't one. A human arrangement built around a generated stem belongs to neither class, and the engine measures the finished mix as a single signal. Expect mid-range probabilities, low confidence, and sections that score differently from each other. We report hybrids as a separate case rather than forcing a verdict.
Can AI-generated vocals be detected?
Partly, and less reliably than full instrumentals. Synthetic singing often shows unnaturally even breath and consonant behaviour and a very stable pitch centre. This engine is tuned for complete music, not isolated speech, so a spoken clip or voice note is outside its scope and should go to a dedicated speech tool instead.
Platforms, policies and consequences
Does Spotify detect AI music?
Spotify has not published a detection method, and it does not ban AI-assisted music as such. What it does act on is artificial streaming, impersonation and spam uploads. Distributors sitting between you and Spotify apply their own screening. Assume disclosure obligations sit with you rather than with a platform's detector.
Does YouTube require AI disclosure?
YouTube requires creators to disclose realistic synthetic or altered content in the upload flow, and it can add a label itself. Music-specific rules also cover synthetic voices of real artists. Disclosure is about realism and likeness rather than whether a tool was used, so read the current policy against your specific upload.
Will a distributor reject AI music?
Distributors including DistroKid and TuneCore reject uploads for impersonation, unauthorised voice clones, spam-scale releases and metadata abuse, not for using a generator. Rejections most often cite policy categories rather than a detection score. Keep your own record of how a track was made; it is far more useful than any detector output.
Is an AI detection result legal evidence?
No. A probability derived from acoustic measurement is not proof of authorship and should not decide a copyright claim, a takedown, a grade or someone's employment. Use it as one input alongside project files, session history, stems, timestamps and direct testimony — the kinds of evidence that actually document a process.
How should a journalist verify an AI music claim?
Run the highest-quality file you can obtain, record the probability, confidence and engine build, and then treat that as one data point. Seek project files, stems, upload timestamps, distributor records and on-record statements. Publish the detector's limitations alongside its number, and never name a person as an AI user on a score alone.
Using this tool
What file formats and lengths work best?
Lossless sources work best: WAV, FLAC or AIFF. MP3, M4A and OGG are accepted but analysed with lower confidence, because encoding removes detail the measurements depend on. Around 30 seconds of continuous music is the practical minimum, and a full track is better, since the engine scores several sections and compares them.
Can I check a Spotify or YouTube link?
No. The tool analyses a local audio file you already have, and it does not fetch or download streams. That is partly a rights question and partly a quality one: a re-encoded stream rip is exactly the kind of degraded source that produces unreliable readings. Use an original master or the highest-quality file you own.
Is there an API for AI music detection?
Not currently. The engine runs client-side by design, which is what keeps audio on your device, and a hosted API would reverse that. Machine-readable material we do publish includes the benchmark protocol at /benchmark.json under CC BY 4.0. If you need programmatic screening, say what for — it shapes whether it should exist.
Why do two detectors disagree about the same song?
Because they measure different things and were tuned on different material. One may weight high-frequency behaviour, another timing regularity, another a learned embedding. Different thresholds then convert similar measurements into opposite labels. Disagreement between tools is normal and is itself evidence that a single score should not be treated as settled.
Still not answered?
The forensics glossary defines every term used in a report, the limitations page lists each known failure mode, and the benchmark shows exactly which figures have and have not been measured. If your question is missing, send it over and it gets added here rather than answered privately.
Cite this page
Quotation with attribution is welcome. Please keep the wording of factual claims intact and link back to the source page.
AI Music Detector. “AI Music Detection Questions, Answered Straight.” Updated August 2026. https://aimusicdetector.co/questions