egyptian-arabizi-franco

Egyptian Arabizi (Franco-Arabic, "Franco") → Arabic, offline, on a CPU:

ezayak 3amel eh       →  ازيك عامل ايه
3andy el meeting bokra →  عندي الmeeting بكرة

A small character-level transformer (about 3M parameters, bundled with the package, no internet needed) plus a few rules around it: English work and tech words stay in Latin letters, numbers, punctuation and emojis pass through, and stretched letters (awyyyy) are shortened before conversion.

Install

pip install egyptian-arabizi-franco

Python 3.9+. Depends only on onnxruntime and numpy (no PyTorch).

Use

from egyptian_arabizi_franco import convert

convert("ezayak 3amel eh")                       # 'ازيك عامل ايه'
convert(["yalla bina", "el meeting bokra"])      # a list in, a list out (faster than one by one)

The first call loads the model (a second or so); later calls reuse it. For more control, keep your own converter:

from egyptian_arabizi_franco import Converter

c = Converter(threads=2)            # limit CPU threads
c.convert("msh fahem 7aga")

raw = Converter(raw=True)           # the model alone, without the rules around it

From the command line:

egyptian-arabizi-franco "ezayak 3amel eh"
cat chat.txt | egyptian-arabizi-franco          # one line in, one line out

How good is it?

On held-out, human-written Egyptian Arabizi: about 74% of words and 37% of whole sentences exactly right (version 0.1.0). Typical mistakes are long vowels (fahem → فهم instead of فاهم) and letters Arabizi writes the same way (s for both س and ص). Results, charts and the training code: github.com/BackendNeuron/egyptian-arabizi-franco.

Licence

MIT. The model was pre-trained on text from the Egyptian Arabic Wikipedia (CC BY-SA 4.0).