100% local — your file never leaves your browser
Podcast Transcript Generator
Turn a podcast episode into text for free — it runs in your browser, so the audio never leaves your device and there is no length limit.
- Free
- No sign-up
- No watermark
How it works
- 01
Add the episode
Pick the MP3, WAV or M4A from your device, or the video file if you record on camera. It is read straight from disk with no upload.
- 02
Pick the spoken language
Choose the language rather than letting it be guessed. Long episodes are split into overlapping windows and stitched back together automatically.
- 03
Copy or export
Copy the text for show notes, or export SRT and VTT when you need timestamps for chapters, clips or an audiogram.
Why choose TranscriptSnap
Episode length is not metered
Two hours costs the same as two minutes, which is nothing. Long episodes are split into overlapping windows and stitched back together, so nothing is lost at the seams.
Unreleased episodes stay unreleased
Transcription usually happens before publication — embargoed guests, uncleared interviews, segments that may be cut. The audio is read from your disk here and never sent to a server.
Timestamps become chapters and clips
Export SRT or VTT and you have the markers for chapter links, the timings for pulling clips, and verbatim quotes for show notes rather than approximations from memory.
No account, no per-episode cost
No sign-up and nothing stored on our side. Podcasting already has enough subscriptions attached to it; transcription does not need to be another one.
Good to know
What the transcript is really for
Almost nobody wants the transcript itself. They want what it unlocks. Show notes written from what was actually said rather than remembered a week later. A searchable record, so the one exchange worth quoting can be found without scrubbing through two hours of audio. Text for listeners who are deaf or hard of hearing, which is the reason a transcript belongs on the episode page regardless of everything else. And raw material for the clips, quote cards and newsletter section that a single episode is supposed to feed.
Episode length and your device
There is no server-side limit here because there is no server, which changes where the ceiling sits. Speech models work on short windows, so a long episode is split into overlapping chunks and reassembled — the overlap is what stops sentences from being cut in half at the seams. The real constraint is your own memory: a two-hour episode is comfortable on a desktop and can be heavy on a phone. If a very long file stalls, splitting the audio in any editor and running the halves works and keeps everything local.
The speaker problem, said plainly
This tool does not label who is speaking. Speaker separation is a second model that is not practical to run inside a browser tab, so a two-person interview comes out as one continuous stream of text with no marker where the voice changes. For a solo episode that costs nothing. For a panel it costs real editing time. If speaker labels are the whole point of transcribing for you, a server-side tool does that job better, and it is worth weighing that honestly against where the audio ends up. What speaker labelling does and when you actually need it
Guest names are where it breaks
Accuracy on podcast audio is usually high — it is mixed for voice, recorded close to a microphone, and edited. The errors cluster somewhere specific: names. Your guest's surname, their company, the book they mention, the technical term that is the whole point of the segment. The model has no context to check any of that against and will confidently write something plausible instead. The efficient fix is a find-and-replace pass over the handful of proper nouns in the episode before you read anything line by line. Why speech models produce confident, invented words
Unreleased episodes stay unreleased
Episodes get transcribed before they are published, which is the window in which they are most sensitive — an embargoed guest, an interview that has not been cleared, a segment that may be cut. Because the model runs in this browser tab, the file is read from your disk and never sent anywhere. There is no upload to secure, no account to breach and no retention policy to trust, and you can check that in the network panel while it runs.
From transcript to show notes
The transcript is a first draft of the episode page, not the page itself. The workflow that saves the most time is to read it once at speed with the timestamps visible, mark the three or four moments worth linking to, and write the summary from those rather than from the top. Timestamps also give you chapter markers almost for free, and the quotes you pull are verbatim rather than approximated. A working process for transcribing an episode
Frequently asked questions
Is this podcast transcript generator free?
Yes, and unlimited. Transcription runs on your own device, so there is no per-minute cost to pass on and no episode cap.
How long an episode can it handle?
There is no imposed limit. Long episodes are chunked automatically; the practical ceiling is your device's memory, so a desktop handles multi-hour files more comfortably than a phone.
Is my episode uploaded anywhere?
No. The file is read from disk by your browser and transcribed in the same tab. You can confirm it in the browser network panel.
Does it separate the host from the guest?
No. Speaker labelling needs a second model that is not practical in a browser, so the transcript is one continuous stream.
Which file formats work?
MP3, WAV, M4A, AAC, OGG and FLAC, plus video files like MP4 and MOV if you record on camera.
How accurate is it on podcast audio?
High, because podcast audio is mixed for voice. Expect errors to concentrate on names, companies and technical terms rather than ordinary speech.
Can I get timestamps for chapters?
Yes. Export SRT or VTT, which both carry timestamps. The plain TXT export is continuous text without them.
Do I need an account?
No. There is no sign-up and no history, because there is nothing stored on our side to sign in to.
A free podcast transcript generator that runs on your own machine
Every episode should have a transcript, and the reasons stack up quickly: listeners who are deaf or hard of hearing depend on it, search engines can read it where they cannot read audio, and a single episode is supposed to feed show notes, clips, quote cards and a newsletter section that all start from text. What usually stops people is the friction — an account, a per-minute charge, an upload of an episode that has not aired. Transcribing a podcast here removes all three, because the speech model runs in your browser rather than on our servers. The trade is honest: no speaker labels, and long episodes lean on your device rather than a data centre.