Detect WellSaid Labs AI voices.
Suspect a clip was made with WellSaid Labs? Run it through the free detector to check whether the voice is AI-generated. WellSaid Labs in short: broadcast-grade corporate voiceover TTS with a curated library of studio voices.
WellSaid Labs, and why it shows up in suspicious audio
WellSaid Labs is a studio text-to-speech platform aimed at corporate training, product videos, and advertising. Its voices are polished and consistent, which is why they are common in e-learning and explainer content.
That studio consistency, the thing that makes the voices useful for narration, is also a trait a detector can key on when a clip is passed off as a real recording.
Where you tend to see it: E-learning, corporate video, and advertising voiceover.
WellSaid Labs is a legitimate product; misuse is the problem, not the tool. You can read about it on the official WellSaid Labs site.
How to tell a WellSaid Labs voice
The human ear is unreliable on current WellSaid Labs audio. These are the kinds of artifacts a detector is trained to pick up.
- 01Unwavering studio delivery, with less spontaneous variation than a real narrator.
- 02Recurring stock-voice timbres that turn up across unrelated clips.
- 03Cleaner phoneme transitions than natural speech.
- 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.