About accuracy in transcription
“Accuracy” isn’t just a number — it’s whether your transcript reflects what was actually said. Here’s how accuracy is measured, what reduces it, and how to get better results with Transkribe.
What transcription accuracy means
Accuracy describes how closely a transcript matches the original recording: the right words, the right speaker, and (ideally) the right structure. A readable transcript with incorrect words can still be misleading — especially for quotes.
How accuracy is measured
Accuracy is often expressed as a percentage. Under the hood, common error types include:
- Omissions: missing words or phrases.
- Insertions: extra words added by mistake.
- Substitutions: the wrong word (often from similar sounds).
- Speaker attribution errors: the right words but assigned to the wrong speaker.
- Punctuation/formatting: changes meaning or reduces readability.
Why 100% accuracy is unrealistic
Real speech is messy: people interrupt each other, mumble, switch languages mid-sentence, and speak in noisy environments. Even human transcribers make judgment calls and occasional mistakes.
Biggest factors that affect accuracy
| Factor | How it affects transcripts | What to do |
|---|---|---|
| Audio quality | Noise, echo, and low volume increase misheard words. | Use a better mic, reduce background noise, record closer to the speaker. |
| Overlapping speech | Models can’t reliably separate voices when people talk over each other. | Encourage turn-taking, record separate tracks if possible. |
| Accents & dialects | Uncommon speech patterns can increase substitutions. | Select the correct language, keep audio clean, review key sections. |
| Names & jargon | Proper nouns and domain terms can be misspelled or swapped. | Quickly search + correct names/terms after transcription. |
| Recording environment | Wind, traffic, cafes, and reverb reduce clarity. | Pick quieter spaces; avoid open rooms; use soft furnishings to reduce echo. |
How Transkribe helps you get better accuracy
The most effective workflow is: generate a transcript fast, then do a light review for the edge cases. Transkribe is designed to support that workflow with a clean transcript output and easy exporting.
- Fast first draft: get a transcript in minutes.
- Searchable text: find and fix names/jargon quickly.
- Export-ready: use transcripts in your writing/editing workflow immediately.
Practical tips to improve accuracy today
- Get closer to the mic (distance matters more than you think).
- Reduce overlap (one voice at a time where possible).
- Record in a quieter place (or use a lapel mic outdoors).
- Speak a little slower (especially for key names and numbers).
- Review proper nouns (people, places, organizations).
When should you consider human review?
If you need certified transcripts, or your audio is extremely noisy/technical, you may still want human review after generating an AI transcript. For most workflows, AI + quick edits is the sweet spot.