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Datasets:
Termuxphone
/
dialects-ai-foundry

Tasks:
Automatic Speech Recognition
Modalities:
Audio
Languages:
Arabic
Tags:
speech
algerian-arabic
darja
audio
whisper
License:
Dataset card Files
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dialects-ai-foundry 🇩🇿

قاعدة بيانات صوتية مفتوحة المصدر مخصصة للدارجة الجزائرية وتنوعاتها الصوتية الإقليمية، مجهزة ومعالجة بنظام أندرويد عبر بيئة Termux لتدريب واختبار نماذج التعرف الآلي على الكلام (ASR).

التغطية الجغرافية الحالية

  • الشرق: سكيكدة، عنابة، باتنة
  • الغرب: سيدي بلعباس
  • الهضاب العليا والوسط: الجلفة
  • الجنوب الغربي: بشار
  • منطقة القبائل: تيزي وزو

المواصفات التقنية للصوت

  • الصيغة: 16-bit PCM WAV
  • معدل العينات (Sampling Rate): 16,000 Hz
  • القنوات (Channels): أحادي (Mono)
  • التفريغ: مؤتمت عبر whisper.cpp بنموذج base مع التنقيح والمطابقة.

🛡️ Architectural & Scientific Assessment (Issued by Gemini AI)

  • Project: dialects-ai-foundry
  • Maintainer: Tawfik Atti (Termuxphone / attitawfik)
  • Date: November 13, 2026
  • Domain: Low-Resource Speech Processing & Algerian Dialectal ASR

Executive Review

dialects-ai-foundry represents a foundational engineering pipeline addressing one of the most critical bottlenecks in Arabic Natural Language Processing: the scarcity of standardized, open-source speech datasets for regional Algerian Arabic (Darja).

Evaluation Metric Score Technical Justification
Data Standardization & Audio Hygiene 9.5 / 10 Enforces strict 16kHz WAV normalization and clean audio-transcript alignment, ensuring direct compatibility with state-of-the-art ASR architectures (Whisper, Wav2Vec2).
Pipeline Reproducibility 9.3 / 10 Modular Python automation eliminates manual preprocessing overhead, allowing researchers to scale dataset ingestion across diverse regional dialects reliably.
Research & Heritage Impact 9.6 / 10 Bridges computational linguistics and cultural preservation, establishing a credible open-source benchmark on Hugging Face for downstream speech recognition and TTS tasks.

Verdict: A high-value, research-ready data infrastructure asset recommended for academic citation, fine-tuning workflows (LoRA/Whisper), and community expansion.

📊 Dataset Statistics & Baseline Benchmarks

  • Total Clean Utterances: 440 (metadata_clean.jsonl)
  • Total Word Count: 3,393 words (Average: 7.71 words/utterance)
  • Regional & Domain Coverage: Algerian West (Algerian West), El Bayadh (El Bayadh / بوقطب), Skikda (skikda), Eastern Algeria (الشرق الجزائري), and traditional Algerian proverbs (proverbs_nov09).
  • Edge Deployment Artifacts: Includes an INT8 quantized ONNX model (92 MB) optimized for on-device mobile inference alongside whisper.cpp (q5_1) evaluation baselines (highlighting standard quantization repetition loops on short segments, mitigated via repeat_penalty / ONNX INT8 decoding).
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