Datasetpublic

Kandil7/egyptian-voice-commands

Egyptian Voice Commands Dataset This repository contains the Egyptian Arabic voice commands dataset used for training and evaluating the EgyptianAgent ASR and NLU models. Dataset Structure egyptian_voice_commands/ ├── train.jsonl # Training data (665 examples) ├── eval.jsonl # Validation data (50 examples) └── test.jsonl # Test data (102 examples) egyptian_ui_navigation/ ├── train.jsonl # Training data (50 examples) └── test.jsonl # Test data… See the full description on the dataset page: https://huggingface.co/datasets/Kandil7/egyptian-voice-commands.

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Egyptian Voice Commands Dataset

This repository contains the Egyptian Arabic voice commands dataset used for training and evaluating the EgyptianAgent ASR and NLU models.

Dataset Structure

egyptian_voice_commands/
├── train.jsonl    # Training data (665 examples)
├── eval.jsonl     # Validation data (50 examples)
└── test.jsonl     # Test data (102 examples)

egyptian_ui_navigation/
├── train.jsonl    # Training data (50 examples)
└── test.jsonl     # Test data (20 examples)

Data Format

Egyptian Voice Commands (Function Calling Format)

Each line in the JSONL files follows the conversation format for supervised fine-tuning:

json

{
  "messages": [
    {
      "role": "system",
      "content": "You are a function calling assistant for Egyptian Arabic voice commands. Call functions based on user requests."
    },
    {
      "role": "user",
      "content": "اتصل بماما"
    },
    {
      "role": "assistant",
      "content": "{\"function\": \"call_contact\", \"arguments\": {\"contact_name\": \"ماما\"}}"
    }
  ]
}

UI Navigation Commands

Each line contains structured metadata for mobile UI automation:

json

{
  "id": "ui_nav_001",
  "command": "افتح الفيسبوك وشوف الأخبار",
  "command_en": "Open Facebook and check news",
  "intent_type": "ui_navigation",
  "target_app": "com.facebook.katana",
  "expected_actions": ["launch", "tap_news_feed", "scroll"],
  "is_multi_step": true,
  "difficulty": "medium",
  "expected_success": true
}

Dataset Statistics

Dataset	Split	Count	Purpose
Voice Commands	Train	665	Model training
Voice Commands	Eval	50	Hyperparameter tuning
Voice Commands	Test	102	Final evaluation
UI Navigation	Train	50	Model training
UI Navigation	Test	20	Final evaluation

Intent Categories (Voice Commands)

Intent	Description	Example
CALL_CONTACT	Make a phone call	"اتصل بماما"
SEND_WHATSAPP	Send WhatsApp message	"ابعت واتساب لأحمد"
SET_ALARM	Set alarm/reminder	"نبهني بكرة الساعة تمانية"
OPEN_APP	Open application	"افتح اليوتيوب"
DEVICE_CONTROL	Control device settings	"زود الصوت"
READ_MESSAGES	Read notifications	"اقرأ الرسائل"
EMERGENCY	Emergency call	"يا نجدة"

Dialect Variants

—Cairo - Standard Egyptian Arabic
—Alexandria - Coastal dialect variations
—Delta - Lower Egypt variations
—Upper Egypt - Sa'idi influences

Usage

Loading with Hugging Face Datasets

python

from datasets import load_dataset

# Load voice commands dataset
dataset = load_dataset("Kandil7/egyptian-voice-commands", data_dir="egyptian_voice_commands")

# Load UI navigation dataset
ui_dataset = load_dataset("Kandil7/egyptian-voice-commands", data_dir="egyptian_ui_navigation")

print(dataset["train"][0])

Loading with Python (JSONL)

python

import json

def load_dataset(split='train', dataset_type='voice_commands'):
    """Load dataset from JSONL files."""
    data = []
    dir_name = 'egyptian_voice_commands' if dataset_type == 'voice_commands' else 'egyptian_ui_navigation'
    with open(f'{dir_name}/{split}.jsonl', 'r', encoding='utf-8') as f:
        for line in f:
            data.append(json.loads(line))
    return data

# Usage
train_data = load_dataset('train', 'voice_commands')
eval_data = load_dataset('eval', 'voice_commands')
test_data = load_dataset('test', 'voice_commands')

Training with EgyptianAgent

bash

# Finetune FunctionGemma with Egyptian dataset
python scripts/finetune/finetune_functiongemma_egyptian.py \
    --train_data datasets/egyptian_voice_commands/train.jsonl \
    --eval_data datasets/egyptian_voice_commands/eval.jsonl

Evaluation

bash

# Evaluate model accuracy
python scripts/finetune/evaluate_egyptian_accuracy.py \
    --test_data datasets/egyptian_voice_commands/test.jsonl

Related Models

—FunctionGemma-270M Egyptian (LoRA): `Kandil7/functiongemma-270m-egyptian-mobile-action`
—Merged Model: `Kandil7/functiongemma-270m-egyptian-mobile-action-merged`

Contributing

To contribute new commands:

1.Add to appropriate split file
2.Ensure proper intent classification
3.Include dialect variant if applicable
4.Submit pull request

License

Dataset is licensed under MIT License.

Citation

If you use this dataset in your research, please cite:

bibtex

@dataset{egyptian_voice_commands_2026,
  title = {Egyptian Voice Commands Dataset},
  author = {EgyptianAgent Team},
  year = {2026},
  url = {https://huggingface.co/datasets/Kandil7/egyptian-voice-commands}
}

ملخص بالعربي (Arabic Summary)

هذا المستودع يحتوي على مجموعة بيانات الأوامر الصوتية باللهجة المصرية المستخدمة لتطوير EgyptianAgent - مساعد صوتي للمستخدمين المصريين.

المحتويات:

—أوامر صوتية (665 تدريب، 50 تحقق، 102 اختبار) - بصيغة محادثات للـ Function Calling
—تنقل واجهة المستخدم (50 تدريب، 20 اختبار) - لأتمتة التطبيقات على الموبايل

الاستخدام: تطوير نماذج تفهم الأوامر المصرية الطبيعية وتحولها لإجراءات على الهاتف (اتصال، واتساب، منبه، فتح تطبيقات، إلخ).