YouTube transcript generator
Give it a YouTube link and it produces a readable transcript in seconds — timestamped by default, or plain if you prefer. Free, unlimited, and no account required.
Free · no sign-up · unlimited
How it works
Paste a link
Any public YouTube video works, of any length. Playlist and channel links are handled elsewhere in the app.
Choose the output
Leave the language as the original, or pick one of 50+ to translate into. Timestamps can be toggled once the transcript loads.
Read or send it to AI
Read it directly, or hand it to the AI tools to produce a summary, notes or flashcards.
Timestamped or plain: which you want depends on the job
A timestamped transcript keeps each line tied to the moment it was spoken. That is what you want when the transcript is a means of navigation — finding the two minutes of a ninety-minute talk that matter, or citing a claim by timecode so someone else can verify it.
Plain text is better when the transcript is something you are going to read start to finish, or feed to something else. Timecodes interrupt the flow of prose and add noise to anything that processes the text afterwards.
| Timestamped | Plain | |
|---|---|---|
| Finding a specific moment | Good | Poor |
| Reading straight through | Distracting | Good |
| Citing a source | Good | Weak |
| Feeding to an AI summary | Adds noise | Good |
Long videos, and where accuracy actually breaks down
Length is not the constraint people expect. A three-hour lecture generates a long transcript, but generating it is no harder than a three-minute clip — the caption track already exists either way.
Accuracy is the real variable, and it depends on how the captions were made. When speech recognition produced them, error rates climb sharply with accented speech, overlapping speakers, technical jargon and background music. A single misrecognised term can repeat throughout a transcript, because the same model made the same mistake every time the word was spoken.
The practical consequence: skim a transcript before trusting it. If the speaker's name or the subject's key terminology look wrong in the first paragraph, they will be wrong throughout.
What translation does to a transcript
Translating is not a cosmetic layer over the text. It changes the object you are holding, and the differences are worth knowing before you rely on it.
Sentence boundaries move. Languages package ideas differently, so a clause that occupied one line may occupy two, or half of one. That is exactly why per-line timings do not survive translation: the original cue boundaries no longer describe the translated text.
Errors compound quietly. If the caption track misheard a technical term, the translation faithfully renders the wrong word, and the result reads as confidently as the correct version would. In the original you might have noticed the oddity; translated, the trace is gone.
Register drifts. Machine translation tends toward neutral, slightly formal phrasing, so a casual speaker comes out sounding like a press release. For comprehension that rarely matters. For quoting someone, it matters a great deal.
Working through several videos at once
One transcript is a task. Twenty is a project, and the thing that makes it manageable is deciding what you are looking for before you start rather than reading each one in turn.
For a research pass — surveying what a channel or a conference covered — the efficient order is to generate a short summary of each video first and read only the transcripts that survive that filter. Reading twenty full transcripts to find the three that matter is the slow route to the same place.
For a series where the videos build on each other, the opposite applies: read them in order, because a summary of episode four assumes you know episode three and will not tell you so.
Either way, keep each transcript at its own address rather than accumulating them in one place. A shareable per-video page means you can send someone the exact source of a claim, and coming back to it later costs nothing because the result is cached.
Playlist handling in the app takes a playlist link and works through it, which is worth using instead of pasting links one at a time when the list is long.
What this can't do
- Output quality is bounded by the caption track. This tool reads captions; it does not re-recognise the audio to improve on them.
- Videos without captions produce nothing — there is no track to read.
- Translated output loses per-line timing, so timestamps are unavailable when you translate.
- Transcripts are displayed for reading only; there is no export.
Frequently asked questions
How long does it take?
- Usually one to three seconds. Videos that have been read before are close to instant.
Is there a limit on video length?
- No. Length affects how much there is to scroll, not whether it works.
Does it work for any language?
- It works wherever YouTube has a caption track. Translation into 50+ languages is available on top of that.
Can I generate transcripts in bulk?
- Playlist processing is available in the app for signed-in users.
Do I need an extension?
- No, the web version needs nothing installed. A Chrome extension exists if you prefer working directly on the YouTube page.