AI Audio Transcriber Free — Transcribe MP3, WAV, and More in Your Browser

What Makes This Transcription Tool Different

Most transcription tools work by uploading your audio to a cloud server, where it is processed by a speech recognition engine and the transcript is sent back. This means your audio — which may contain meetings, interviews, medical notes, or personal conversations — is transmitted over the internet and processed on someone else's infrastructure.

This tool works differently. It uses Transformers.js to run OpenAI's Whisper-tiny model entirely in your browser using WebAssembly. The audio is decoded using the Web Audio API and processed locally — no audio data ever leaves your device.

Supported Audio Formats

How to Transcribe an Audio File

1. Open the tool. Go to the AI Audio Transcriber. No login required.
2. Upload an audio file. Click the dropzone or drag a file onto it. Supported formats: MP3, WAV, M4A, WebM, OGG, FLAC.
3. Click Transcribe Audio. On first use, Whisper-tiny (~75 MB) downloads and caches in your browser. A progress bar shows the download status.
4. Review and edit the transcript. The text appears in an editable textarea. Correct errors, remove filler words, and format as needed.
5. Copy or download. Use the Copy button or Download .txt to save your final transcript.

Advanced Use Cases

Transcribing meeting recordings

If your video conferencing tool exports recordings, extract the audio track first using the MP4 to MP3 Converter, then upload the MP3 here. Whisper handles multi-speaker audio but may attribute speech to a single speaker in the transcript — manually mark speaker turns after generation if needed.

Creating captions and subtitles

Generate the raw transcript here, then format it with timecodes manually in a text editor for use as SRT or VTT subtitle files. For automated timecode generation, a dedicated subtitle tool with Whisper's timestamp output would be needed.

Converting voice memos to notes

iPhone and Android voice memos export as M4A or MP3 files. Upload them here to convert spoken notes to text — useful for ideas captured while driving, exercising, or away from a keyboard.

Transcribing interviews and podcasts

For interview transcription, clear audio with one speaker at a time produces the best results. Edit the transcript to attribute quotes before exporting. For podcasts with multiple hosts, Whisper will merge all voices into one transcript without speaker differentiation.

Common Questions

Is my audio private?

Yes. The Whisper model runs entirely in your browser. No audio is transmitted to any server. The only network request is the one-time download of the model file from Hugging Face CDN.

How long does transcription take?

After the model is loaded, transcription speed depends on the audio length and your device. On a modern laptop, Whisper-tiny processes audio at roughly 2–4× real time (a 5-minute recording takes 1–2 minutes to transcribe). Older or lower-spec devices will be slower.

How is this different from the Speech to Text tool?

The Speech to Text tool captures live microphone input in real time using the browser's Web Speech API — it requires speaking in the moment and sends audio to a cloud backend. This Audio Transcriber processes uploaded files using a local Whisper model, making it suitable for recordings you already have.