Detect iSpeech AI voices.
Suspect a clip was made with iSpeech? Run it through the free detector to check whether the voice is AI-generated. iSpeech in short: long-standing cloud text-to-speech and voice API used in apps and phone systems.
iSpeech, and why it shows up in suspicious audio
iSpeech is a long-established text-to-speech and voice API used in apps, accessibility tools, and phone systems (IVR). Its voices turn up in automated calls and notifications.
Because it is often delivered over telephony, iSpeech clips arrive compressed, the harder case a detector must handle honestly.
Where you tend to see it: IVR and phone systems, app narration, and automated notifications.
iSpeech is a legitimate product; misuse is the problem, not the tool. You can read about it on the official iSpeech site.
How to tell an iSpeech voice
The human ear is unreliable on current iSpeech audio. These are the kinds of artifacts a detector is trained to pick up.
- 01Production-TTS pacing that does not react to meaning.
- 02Artifacts that persist through telephony-grade compression.
- 03Uniform spectral balance across a clip.
- 04Even, unvarying energy across long passages.
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.