A clip lands in your inbox and the desk wants to know by four o'clock. Detection is the fastest check you can run and the weakest one to publish on — it speaks to how the audio was produced and says nothing about who is speaking, when, or in what context. This is where it fits in a verification workflow, and where it does not.
Getting this boundary right is the whole job, because the failure mode here is public.
That third exclusion deserves emphasis, because it is the one that burns newsrooms. A recording can be entirely authentic audio and entirely misleading — real sentences from a real occasion, assembled to imply something that was never said. A spoof detector will call that human, correctly, and uselessly. If your actual concern is manipulation rather than synthesis, you are holding the wrong instrument.
Detection is step three, not step one. The cheap questions come first because they resolve more cases.
The language you use travels further than the finding does.
Detection results get flattened in transmission. Whatever hedge you write, a sub-editor may cut it and an aggregator will drop it. So the hedge has to survive being shortened.
| Avoid | Prefer |
|---|---|
| “AI analysis proved the recording was fake” | “An automated detection tool assessed the audio as likely synthetic; the tool is not forensic analysis and its makers say it should not be relied on alone” |
| “99% certain it was AI-generated” | Name the tool and describe the output in its own terms, with the audio conditions stated |
| “Experts confirmed the voice was cloned” | Say who, with what method, and what they actually claimed |
| “The detector cleared the recording” | “The tool found no evidence of synthesis” — which is not the same as authentication |
Two further points worth carrying into copy. First, state the audio conditions: a result on a forwarded, compressed phone recording deserves a different weight from one on an original file, and readers cannot apply that discount if you do not tell them. Second, remember that false positives land on people who record well — professionally produced audio is mastered in ways that strip the untidiness detection looks for, so a polished recording is more exposed to a wrong flag, not less.
The control-recording method: run a known-genuine clip alongside the suspect one and read the gap.
Learn the method →Why we publish no single accuracy percentage, what false positives look like, and how to weigh a result.
See our position →The technical guide: how detection works, and why it generalises poorly to unseen generators.
Read the technical guide →Three checks a day, free, no signup. Your audio is never stored.