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Detect Murf AI AI voices.

Updated July 2026

Suspect a clip was made with Murf AI? Drop it in and get a citable verdict with the model named, in under half a second. Polished corporate-voiceover TTS with a large stock-voice library.

Check a clip freeAll generators
Synthetic detectedMurf AI
Confidence
high
Model
Murf AI
Yes, you can check. Drop the clip into the detector and it returns the probability that the speech was generated by Murf AI, a confidence level, and the named model, in under half a second. It reads the audio's synthesis signature, so it works on cloned and stock Murf AI voices alike, and gives you a citation URL to quote.
What it is

Murf AI, and why it shows up in suspicious audio

Murf AI is a studio text-to-speech product aimed at voiceover and e-learning, with a large library of stock voices. It is common in narrated explainers and training content, and occasionally in scripted impersonation.

Its stock voices are recognizable once you have heard a few, and the polish that makes them good for e-learning is itself a detectable trait.

Where you tend to see it: E-learning, explainer videos, and corporate narration.

Murf AI is a legitimate product; misuse is the problem, not the tool. You can read about it on the official Murf AI site.

The tells

How to tell a Murf AI voice

The human ear is unreliable on current Murf AI audio. These are the signals a detector weighs. We report which ones drove the verdict rather than handing you a bare number.

  • 01Polished, unwavering delivery. Real narration varies in ways production TTS does not.
  • 02Reused stock-voice timbres that recur across unrelated clips.
  • 03Synthesis artifacts in transitions that a model reads even when the clip sounds clean.
  • 04A studio-uniform noise floor with no room signature.
Spectral view · artifacts concentrate where synthesis smooths what a human voice would not
How the detector identifies Murf AI

A verdict you can cite, not a vibe

The detector reads the audio, not the speaker. Cloning or stock voice, clean or compressed, it looks for the synthesis signature and attributes the source.

Step 1

Drop the clip

Upload a file or paste a URL. MP3, WAV, M4A, WebM, or the audio track of a video. About half a second of clear speech is enough.

Step 2

The model scores it

The same model behind the public detector reads the acoustic signature and weighs the artifacts, then attributes the source, e.g. Murf AI, when it recognizes it.

Step 3

Get a citable verdict

You get a probability, a confidence level, the named model, and a permanent citation URL you can quote, file, or subpoena.

0.48s
Median verdict
99%
Accuracy on clean audio
24+
Generators covered
24h
Audio deleted after
If a clip turns out synthetic

What to do next

A verdict is evidence, not a verdict of intent. Save the result to get a permanent citation URL and a one-way audio fingerprint you can reference later without storing the file. If you are a journalist or investigator, cite the verdict alongside your own reporting; if this is a suspected scam, treat the contact as unverified and confirm through a channel you already trust. The FTC's advice on suspected scam calls is a sensible baseline.

Building this into a workflow? The API returns the same verdict as JSON with webhooks for bulk jobs, and the browser extension checks audio in place on WhatsApp Web, YouTube, and podcasts.

FAQ · Murf AI

Common questions

Stock voice or cloned, does it matter?
No. The detector reads the synthesis, not the speaker, so both are in scope.
How fast is a verdict?
About half a second of compute on a typical clip.
Can you detect Murf inside a video?
Yes. The detector reads the audio track, so video files work too.
Is there a free check?
Yes, a single verdict is free.
Do you name the model?
When we recognize Murf we name it; ambiguous clips return 'unknown synthesis'.
Detect another generator

We attribute 24+ voice models

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See all generators → How to detect AI voices → Spotting AI voice scams →

Is this a Murf AI voice? Find out.

Free verdict, model named, in under a second. No card to start.

Open detectorUse the API