WAV to text for serious recordings

WAV is the format of people who care about their audio: studio sessions, field recordings, voice-over takes, courtroom and archive digitizations. Those files are big — a single hour of uncompressed audio can pass 600 MB — which makes “upload it to our server” a terrible workflow.

This tool skips the upload entirely. The WAV is decoded in your browser and transcribed on your own hardware, so a huge file starts processing immediately instead of crawling up your connection. Your files are never uploaded — everything runs on your device.

Checking what this browser supports…

How to transcribe a WAV file

  1. Drop in the WAV

    Any sample rate or channel count works — the tool downmixes and resamples automatically before transcription.

  2. Processing starts instantly

    No upload wait, even for very large files. The transcript appears progressively, with progress shown against the recording’s length.

  3. Refine and export

    Correct technical vocabulary inline, then export TXT for documents, SRT/VTT for subtitling, or JSON with precise segment timings.

Built for heavyweight files

No upload bottleneck

A 600 MB session file would take ages to upload. Reading it locally takes seconds — the only real work is the transcription itself.

Any sample rate in

44.1 kHz CDs, 48 kHz video audio, 96 kHz masters, 8 kHz telephone archives: everything is resampled correctly under the hood.

Masters stay yours

Unreleased recordings and client sessions never touch a third-party server. What you recorded stays exactly where you put it.

WAV transcription questions

Is there a file-size limit?
No hard limit is enforced. Very large files are bounded by your device’s memory; the audio is processed in windows to keep usage steady during transcription itself.
Do high sample rates improve the transcript?
Not really — speech models listen at 16 kHz, and your file is resampled to that automatically. High sample rates don’t hurt, but they don’t add accuracy either.
Stereo, mono, multi-channel?
All fine. Channels are averaged down to mono before transcription, which is what speech recognition expects.
What model does the recognition?
OpenAI’s open-source Whisper model, executed locally in your browser by our open-source engine. Nothing about your audio is sent out to run it.
Can I transcribe several takes in a row?
Yes — drop the next file as soon as the previous transcript is done (or cancel mid-way). The model stays loaded, so follow-up files skip the download and start faster.