Updated October 2026 · AI audio explained
AI transcription is often good on clear speech, but accuracy depends on the audio, the accents, the names and the technical terms. Expect errors on names, numbers and specialist words, and check the transcript against the audio before you publish any quote.
AI transcription has become quick and useful, which makes it tempting to publish a transcript without checking it. Accuracy varies, and the errors that matter most, such as names and numbers, are the ones that are easiest to miss. A short check turns a rough transcript into a reliable one.
The biggest factors are the recording quality, how many people speak at once, and the vocabulary. A clean recording of one speaker with common words is the easiest case. Background noise, crosstalk, strong accents and many technical terms all make errors more likely.
Some transcription tools run on your own device, and some send the audio to a server. Read what each tool does with your files before you upload an interview. A transcript of a private conversation needs more care than a public lecture.
No transcript is perfect, and accuracy claims depend on the test used. Check your own interviews, and treat the transcript as a draft for editing rather than a final record. The show notes post covers using a transcript for publishing.
Record voice-overs with live noise removal, or clean an existing file. Runs in your browser, nothing is uploaded.
Only after checking, especially names, numbers and quotes against the audio.
Similar voices, crosstalk and poor audio make speaker labels harder. Fix them by hand.
It can increase the errors. Check those sections more carefully.
Yes. It lets you check the quotes and fix errors later.
