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Lecture Transcription

Study ToolsFree · Private

Turn a recorded lecture into a readable, paragraph-broken transcript — upload audio or record from your microphone, entirely on-device using an in-browser AI model. Nothing uploaded.

Nothing is uploaded — all processing happens on your device. No audio ever leaves this browser tab — transcription runs entirely on-device via an in-browser AI model.

Upload a lecture recording (.mp3, .wav, .m4a) or record one from your microphone.

How to use it

  1. Upload a recorded lecture (.mp3, .wav, .m4a) or record one from your microphone, then stop the recording.
  2. Pick Standard (faster) or Enhanced (more accurate but slower).
  3. Click Transcribe — the first use downloads the AI model (cached after that), then real progress and a time estimate show while it works through the audio.
  4. Toggle timestamps on or off, then copy the transcript or download it as .txt or .srt (captions).

Both models are free and unlimited, no account needed.

How this works

Transcription runs on an AI model right in your browser, automatically using the fastest option your device supports. Long recordings are split into short overlapping pieces so progress and a time estimate are real, not guessed, and so very long lectures don't need to fit in memory all at once.

What this is — and isn't

This is upload-or-record, then transcribe — not live transcription while you're still recording, and it doesn't label different speakers or summarize the content. Those are planned as separate tools. And like any speech-to-text system, accuracy depends on audio quality — always proofread before relying on the transcript, especially for names and technical terms.

Privacy

Your audio never leaves this browser tab. Decoding, transcription, and export all run entirely on your device.

Frequently Asked Questions

How accurate is the transcript?
It depends on audio quality, accents, and background noise — like any speech recognition system, including the paid cloud ones. The Standard model is generally strong for clear speech; the Enhanced model is more accurate but slower. Always proofread before relying on it, especially for names and technical terms.
Why is audio processed in pieces, and does that cause any glitches?
Long audio gets split into short overlapping pieces and transcribed one at a time — this is what makes real progress ("part 4 of 12") and a time estimate possible for long lectures, instead of one opaque black-box call. The overlapping regions are trimmed and stitched back together, but very occasionally a word right at a seam can be slightly duplicated or clipped. It's a minor, honest trade-off for genuine progress visibility on long files.
Does this use my computer's graphics hardware?
It automatically uses the fastest option your browser and device support, and falls back gracefully if not. Either way, everything runs locally — nothing is ever sent anywhere.
Does this do speaker labels, summaries, or live transcription while I record?
Not speaker labels or live streaming transcription yet — this first version is upload (or record, then stop) → transcribe. For a summary or flashcards from the transcript, paste it into the Notes Summarizer & Flashcard Maker, a separate on-device tool built for exactly that.
Is my audio uploaded anywhere?
No. The audio file or microphone recording never leaves your browser tab — decoding, transcription, and export all run entirely on your device.

Related Tools

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Notes Summarizer & Flashcard Maker

Turn lecture notes or a transcript into a short key-points summary or a set of flashcards — generated by a local AI model running entirely in your browser. Nothing uploaded.