⚠️ EXPERIMENTAL WIP – This is a heavily modified fork, purely vibe-coded. Expect bugs, breaking changes, and rough edges.
Try it now: pw.olicorne.org — no installation required.
Browser-based speech-to-text running entirely client-side using NVIDIA's Parakeet TDT 0.6B v3 model (converted to ONNX format by istupakov) via WebGPU/WASM.
- Runs speech-to-text entirely in your browser (nothing sent to servers)
- Supports WebGPU (fast) and WASM (compatible) backends
- Word-level timestamps and confidence scores
- File upload or microphone recording
- Model quantization options (fp32/int8)
- Installable as a PWA (Progressive Web App) for app-like experience
- 🚧 Work in progress
- 🧪 Experimental and unstable
- 📝 Licensed under AGPLv3
- 🎨 Vibe-coded with aider.chat and Claude Code
Parakeet Web includes an experimental dictation mode that post-processes transcriptions using regex rules to clean up spoken punctuation, medical vocabulary, and unit abbreviations. This is especially useful for French medical dictation. It
The regex rules are sourced from the murmure-regex repository by the non profit interhop.org for the Murmure software, which I also use when I can. A single combined CSV file containing all rules is automatically downloaded on container startup.
The rules are in French and cover categories like punctuation, unit abbreviations, clinical exam templates, medication name corrections, and medical vocabulary corrections.
This feature is very early and will improve rapidly.
- Docker: The entrypoint script downloads the single combined
regex.csvfile from the murmure-regex repository on first startup. - Local development: Run
./scripts/download-dictation-regex.shto fetch the rules intoapp/ui/public/dictation-regex/. - Frontend: The app loads the CSV rules at startup via a manifest file and applies them as JavaScript
RegExpreplacements. After regex processing, each line is stripped of leading/trailing whitespace and its first letter is capitalized. Three display modes are available per transcription: Raw, Confidence (heatmap), and Dictation (regex-cleaned). - Custom regex source: Set the
DICTATION_REGEX_SOURCEenvironment variable to override the default Murmure URL. This can be a GitLab-compatible repo URL (e.g.https://framagit.org/interhop/murmure-regex) or a local folder path containing CSV regex files (e.g./path/to/my/regex-csvs). This allows you to iterate on regex rules locally without waiting for upstream changes.
# 1. Copy the example env file and edit it with your own values
cp docker/env.example docker/.env
# 2. Run the demo locally with Docker
sudo docker compose -f docker/docker-compose.yml up- Then visit
http://localhost:5173
If HuggingFace is blocked or unreachable in your environment, you can serve model weights directly from the container:
# 1. Install the HuggingFace CLI and download the model files locally
pip install huggingface-hub
hf download istupakov/parakeet-tdt-0.6b-v3-onnx --local-dir ./fallback_models/istupakov__parakeet-tdt-0.6b-v3-onnx
# 2. In docker/docker-compose.yml, uncomment the volume bind:
# - ./fallback_models/istupakov__parakeet-tdt-0.6b-v3-onnx:/app/ui/public/models/istupakov/parakeet-tdt-0.6b-v3-onnx:ro
# 3. In docker/.env, enable the fallback:
VITE_LOCAL_MODEL_FALLBACK=trueThe downloaded files are git-ignored. When VITE_LOCAL_MODEL_FALLBACK=true is set, the app will check for the local model files on startup and refuse to load if they are missing.
AGPLv3 – See LICENSE file
- ysdede/parakeet.js – Original project this is forked from
- nvidia/parakeet-tdt-0.6b-v3 – The underlying ASR model by NVIDIA
- istupakov/parakeet-tdt-0.6b-v3-onnx – ONNX conversion of the model
- istupakov/onnx-asr – Python reference implementation
- ONNX Runtime Web – Makes browser inference possible
This fork is based on ysdede/parakeet.js – all the heavy lifting and original implementation credit goes there. This would not exist without their excellent work.
