Detect Murf AI AI voices.
Suspect a clip was made with Murf AI? Run it through the free detector to check whether the voice is AI-generated. Murf AI in short: polished corporate-voiceover TTS with a large stock-voice library.
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.
How to tell a Murf AI voice
The human ear is unreliable on current Murf AI audio. These are the kinds of artifacts a detector is trained to pick up.
- 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.
What the detector tells you
The detector reads the audio, not the speaker. Cloned or stock voice, clean or compressed, it looks for the signs of synthesis.
Drop the clip
Upload an MP3, WAV, M4A, OGG, FLAC or AAC file. Three seconds or more of clear speech gives the most reliable result.
The model scores it
The model scores the clip. On longer recordings it scores each segment separately, so you can see which part sounds synthetic.
Read the verdict
You get a verdict on a four-step scale, from Human to AI Generated, plus an AI probability score. It tells you whether the voice is AI-generated, not which tool made it.
What to do next
A verdict is evidence, not proof. Sign in to keep the result in your detection history and share it with a link. If you are a journalist or investigator, use it 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, and a Chrome extension for checking audio in any tab is in development.