Every recording you keep is a document you have not written yet. An interview, a lecture, a client call, a voice memo you left yourself on the way home — the information is in there, but it is locked in a format you cannot search, quote or paste. Converting speech to text is how you unlock it.
There are three practical ways to do it, and the right choice depends far more on your deadline than on your budget.
1. Type it yourself
Manual transcription takes roughly four to six times the length of the audio. A one-hour interview is most of a working day, and that is if the audio is clean and there is only one speaker. The upside is total control; the downside is that nobody who does this regularly keeps doing it.
It still makes sense for very short clips — under two minutes — or when the recording is so noisy that no tool will manage it and you need to guess from context.
2. Dictate in real time
Built-in dictation (Google Docs voice typing, Windows dictation, the microphone key on your phone) writes as you speak. It is excellent for composing new text and poor for transcribing existing recordings: you have to play the audio into a microphone in real time, the tool cannot separate speakers, and any pause or overlap confuses it.
Use dictation to draft. Do not use it to process a recording you already have.
3. Run the file through a transcription tool
This is what most people actually need. You upload the audio or video file, an AI speech model processes it, and you get text back in a fraction of the recording's length. A one-hour file typically takes a few minutes, not a few hours.
The quality question is not "is AI accurate?" but "is AI accurate on your audio?". That depends on four things, and three of them are in your control.
Recording quality
This matters more than the model does. A phone lying on a table between two people in a quiet room beats an expensive microphone in a cafe. If you can, record close to the speaker, away from air conditioning, and off the hard surface that everyone keeps tapping.
Number of speakers
One speaker is easy. Two taking turns is fine. Six people interrupting each other around a table is where every tool struggles, human transcribers included. Speaker identification helps, but it works best when people do not talk over each other.
Accent and vocabulary
Modern models handle accents well. What they do not know is your world: product names, internal acronyms, the surname of the person you interviewed. Expect to fix those, and expect the same mistake to repeat consistently — which means one find-and-replace fixes all of them at once.
Language
If the recording switches languages mid-sentence, tell the tool which language you want out. Automatic detection picks whatever dominates the first minute, and that is not always what you meant.
What to do with the raw transcript
A fresh machine transcript is a first draft, not a finished document. Three passes turn it into something you can send:
- Fix the names. Search for every proper noun once. This is usually 80% of the errors.
- Cut the filler. "You know", "sort of", repeated false starts — the meaning survives without them.
- Add structure. Headings every few minutes of conversation make a long transcript readable and, if you publish it, searchable.
How long it actually takes
For a one-hour recording: a few minutes of processing, then roughly fifteen to thirty minutes of editing. Compared with four to six hours of typing, that is the whole argument.
Try it on your own file
The fastest way to judge accuracy is to run something you already have. Create a free account — 15 minutes of transcription every month, no card required — upload the file, and compare the result against what you remember of the conversation.
If you are choosing between tools, the comparison of transcription software covers what the main options do differently. If you specifically need a video transcript, start with getting a transcript from YouTube.