---
license: mit
language:
- ar
- en
tags:
- whisper
- whisper.cpp
- ggml
- futo
- futo-keyboard
- egyptian-arabic
- code-switching
- acft
base_model:
- IbrahimAmin/code-switched-egyptian-arabic-whisper-small
- mohammedaly22/whisper-large-v3-turbo-egyptian-code-switching
---

# Egyptian Arabic voice input models for FUTO Keyboard

Offline Egyptian Arabic (+ English code-switching) Whisper models, adapted with FUTO's
[ACFT](https://github.com/futo-org/whisper-acft) method and converted to whisper.cpp GGML,
ready to import into [FUTO Keyboard](https://keyboard.futo.org/) / FUTO Voice Input on Android.

Without ACFT, Whisper models loop or repeat on clips shorter than ~15 s inside FUTO. These don't.

## Files

| File | Base | Params | Size | Notes |
|---|---|---|---|---|
| `small_egy_acft_q8_0.bin` | IbrahimAmin/code-switched-egyptian-arabic-whisper-small | 244M | 253 MB | Runs on any modern phone. Recommended default. |
| `small_egy_acft_q5_0.bin` | same | 244M | 168 MB | Smaller, slightly less accurate. |
| `turbo_egy_acft_q5_0.bin` | mohammedaly22/whisper-large-v3-turbo-egyptian-code-switching | 809M | ~570 MB | Noticeably better on dialect and س/ص style ambiguity. Flagship phones (Snapdragon 8 Gen 3 / 8 Elite, Dimensity 9300+) with 12 GB+ RAM. |
| `turbo_egy_acft_q8_0.bin` | same | 809M | ~870 MB | Highest quality, slowest. |

## How to use on Android

1. Install FUTO Keyboard and add Arabic under Settings > Languages.
2. Download one `.bin` to the phone.
3. Open it with FUTO Keyboard (file manager > Open with), or Settings > Languages > Import from file. Assign to Arabic.
4. Tap the mic and speak.

## How they were made

ACFT (audio context fine-tuning, FUTO's method): 2000 steps, lr 1e-6, MSE between decoder hidden
states of the student (dynamic audio context) and a frozen reference (full 30 s context), on ~4 h of
Egyptian speech from `MAdel121/arabic-egy-cleaned`. For turbo only the encoder was trained (decoder
frozen, 8-bit Adam) to fit a single T4. Then whisper.cpp `convert-h5-to-ggml.py` and `whisper-quantize`.

Credit to the fine-tune authors (IbrahimAmin, mohammedaly22) and to FUTO for ACFT. Built in one
Colab session; issues and better Egyptian fine-tunes welcome.