Detect Cartesia AI voices.
Suspect a clip was made with Cartesia? Run it through the free detector to check whether the voice is AI-generated. Cartesia in short: fast, low-latency neural TTS (Sonic) built for real-time voice apps and agents.
Cartesia, and why it shows up in suspicious audio
Cartesia's Sonic is a low-latency neural text-to-speech model built for real-time voice applications and agents. Its speed makes it attractive for live voice bots and, potentially, real-time impersonation.
Real-time generation trades a little fidelity for speed, and that trade leaves its own artifacts a detector can key on.
Where you tend to see it: Real-time voice bots and agents, app voices, and impersonation.
Cartesia is a legitimate product; misuse is the problem, not the tool. You can read about it on the official Cartesia site.
How to tell a Cartesia voice
The human ear is unreliable on current Cartesia audio. These are the kinds of artifacts a detector is trained to pick up.
- 01Timing and micro-latency patterns unlike a naturally recorded human.
- 02Spectral artifacts introduced by streaming synthesis.
- 03Prosodic regularity across a passage.
- 04Consistency a live human voice, affected by room and movement, would not maintain.
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.