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غبيّ
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مكلّخ
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مجلّج
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كبير
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صغير
m8rrs
مهرّس
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مملّ
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صلع
ghliD
غليض
Tebbouzi
طبّوزي
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رقيق
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طويل
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قصير
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زوين
bogos
بوڭوص
khayb
خايب
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هبيل
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مصطّي
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عامر
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جديد
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قديم
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شارف
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صعيب
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قاسح
sa8l
ساهل
m3TTl
معطّل
7a9i9ia
حقيقية
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عادي
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ڭادّ
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بسيط
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معقّد
t9il
تقيل
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واسع
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ناشط
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نقي
3aadil
عادل
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غني
fa9ir
فقير
Tabi3i
طبيعي
mfrou9
مفروق
mch8our
مشهور
fr7an
فرحان
dourijin
دوريجين
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خايف
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ضخم
3imla9
عملاق
za8i
زاهي
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فخور
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راضي
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مرتاح
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معصّب
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مشاغب
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غضبان
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مرڭ
7chman
حشمان
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كالم
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وحيد
mnba8er
منباهر
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مستغرب
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مشوكي
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مروّن
mtredded
متردّد
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عيّان
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طمّاع
anani
أناني
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سخي
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دكي
7akim
حكيم
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نابغة
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أمين
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كدّاب
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غدّار
nSSab
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نيّة
mtfa2l
متفاءل
mtcha2m
متشاءم

Overview

This dataset is a modified version of the Darija Open Dataset (DODa), tailored specifically for the purpose of learning a transliteration mapping from Arabizi Darija text to Arabic letters Darija.

The Arabizi-To-Arabic-Mapping (ATAM) Transliteration Dataset serves as a valuable resource for training models to accurately transliterate Arabizi Darija text into Arabic letters Darija, facilitating natural language processing tasks in the Moroccan dialect.

Key Features:

  • Adapted Structure: The dataset has been meticulously adapted from the original DODa format to focus on the transliteration task, ensuring relevance and effectiveness in training transliteration models.

  • Diverse Text Samples: It encompasses a diverse range of Arabizi Darija text samples, covering various linguistic nuances and expressions commonly found in informal communications.

  • Annotated Transliterations: Each Arabizi Darija text entry is accompanied by its corresponding transliteration into Arabic letters Darija, enabling supervised learning for transliteration mapping.

N.B: We have a One-To-Many relationship as each word in the Arabic letter format can be associated (written) to many others in the Arabizi format.

Usage:

Researchers and developers can leverage this dataset to train and evaluate machine learning models aimed at automating the transliteration process from Arabizi Darija to Arabic letters Darija.

Acknowledgments:

We extend our gratitude to the creators and contributors of the Darija Open Dataset (DODa) for their pioneering work, which serves as the foundation for this transliteration dataset adaptation.

Contact:

For inquiries or contributions related to the ATAM Transliteration Dataset, feel free to reach out.


dataset_info: features: - name: darija dtype: string - name: darija_ar dtype: string - name: english dtype: string splits: - name: train num_bytes: 2705541 num_examples: 67186 download_size: 1793167 dataset_size: 2705541 configs: - config_name: default data_files: - split: train path: data/train-* language: - ar size_categories: - 10K<n<100K

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