MP3 to text, without the upload
MP3 is where the world’s spoken audio ends up: podcast episodes, recorded interviews, lecture archives, old dictaphone files. This page turns those MP3s into searchable, editable text — right here in the browser tab, with nothing sent anywhere.
A one-hour podcast episode would take a while just to upload on most connections. Here there is no upload step at all: the file is read from disk and transcribed on the spot, with the transcript streaming in as it goes. Your files are never uploaded — everything runs on your device.
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How to convert an MP3 to text
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Add your MP3
Drag the file into the tool above. Long episodes are fine — length only costs your machine’s time, not money.
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Let it transcribe in chunks
The recording is processed in 30-second windows, so the beginning of a long interview is readable while the rest is still being worked through.
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Clean up and export
Fix names and jargon with a click, search within the transcript, then export TXT for notes, SRT/VTT for captions, or JSON for further processing.
Made for long-form audio
Podcast-length friendly
No per-minute billing means a full season backlog is just a matter of letting it run. Progress and an ETA keep you informed on longer files.
Compressed audio, handled
MP3’s compression is no obstacle — the decoder your browser already ships handles bitrates from voice memos to studio masters.
Interviews stay confidential
Unpublished interviews and embargoed material never leave the machine. There is no server copy to worry about, because there is no server involved.
MP3 transcription questions
- How long can the MP3 be?
- There is no enforced limit. Practical length depends on your device’s memory and patience — hour-long episodes are routine, and the transcript streams in as it processes so you can start reading early.
- Does low bitrate hurt accuracy?
- Heavily compressed or noisy recordings transcribe less accurately than clean ones — that is true of every transcription system. Speech stays intelligible to the model at bitrates far below typical podcast quality.
- Can I get timestamps for each part?
- Yes. Every segment carries start and end times, visible in the transcript view and preserved in SRT, VTT, and JSON exports.
- What engine does the transcription?
- It is powered by OpenAI’s open-source Whisper model, running in your browser through WebGPU or WebAssembly. Our engine wrapping it is open source as well.
- Why is there no upload progress bar?
- Because nothing uploads. The file is read directly from your disk into the browser’s memory. The only download is the model itself, once, on your first visit.