Offline transcription guide

Local Whisper Transcription in Browser

Run Whisper-style speech recognition locally in your browser with Web Worker execution, model caching, and private on-device media processing.

Start Local Transcription Read Technical Flow
Updated: May 29, 2026

Runtime model

OfflineTranscriber uses browser-side inference through Transformers.js and ONNX Runtime Web. Work runs in a Web Worker so the interface stays responsive during transcription.

Limits

Performance depends on browser support, device memory, CPU/GPU capability, recording length, and source audio quality. Long files may need more time on low-power devices.

Recommended workflow

  1. Open OfflineTranscriber and select your local audio or video file.
  2. Wait for model setup if this is the first run in the browser.
  3. Run transcription locally and keep the tab active while processing.
  4. Review the transcript and export TXT, SRT, VTT, or JSON when available.

Related pages

How Offlinetranscriber Works Read a related privacy-first transcription guide. On Device Transcription Read a related privacy-first transcription guide. Offline Speech to text Open a focused conversion page with the same private local workflow. Mp3 to text Open a focused conversion page with the same private local workflow. Mp4 to text Open a focused conversion page with the same private local workflow.

FAQ

Can this run without uploading recordings?

Yes. The normal transcription workflow processes media locally in the browser and avoids uploading raw files to our app backend.

What should I check before using it offline?

Load the app and model once while online, then keep the same browser profile and site data so cached assets remain available.

What are the main limits?

Large files depend on local memory and compute. Source quality, speaker overlap, and browser support affect speed and transcript accuracy.