Syrinesmati/tunisian-dialect-corpus

Dataset Card for Tunisian Dialect Corpus (Cleaned Arabic-Only)

1. Dataset Overview

1.1 Description

This dataset is a cleaned corpus of Tunisian Arabic dialect text, aggregated from multiple public sources on Hugging Face. It is designed for Continual Pretraining (CPT) and general NLP research.

A dedicated preprocessing pipeline was applied to:

• Normalize text
• Remove noise and artifacts
• Filter non-Arabic content
• Ensure higher overall data quality

The final dataset focuses on Arabic-script Tunisian dialect (ar-TN) with reduced noise and improved consistency.

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1.2 Key Information

Field	Value
Curated by	Syrinesmati
Language(s)	Arabic (Tunisian dialect, ar-TN)
License	Apache-2.0
Format	Parquet
Primary Field	text

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2. Dataset Sources

This dataset is a merged and cleaned derivative of the following public resources:

#	Source	Notes
1	linagora/Tunisian_Derja_Dataset	Transcripts kept as-is
2	atakaboudi/Dialect_of_Tunisia-Work_Collection	—
3	tunis-ai/tunisian-msa-parallel-corpus	—
4	Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred_organiser_Mixed	STT/TTS dataset; target sentences and transcripts kept as-is
5	linagora/linto-asr-ar-tn-0.1	ASR dataset from multiple sources (YouTube_TNScrapped, TunswitchTO, TunswitchCS, ApprendreLeTunisien, Taric, OneStory); sentences kept as-is
6	Tunisian Arabic Dialects Identification — TADI	Binary classification dataset; only rows identified as Tunisian dialect extracted
7	Tunisian Algerian Dialect — TAD (instadeepai/tunbert)	Binary classification dataset; only rows identified as Tunisian dialect extracted
8	khaled123/tunninjaar	Extracted from derja.ninja
9	Hala-Mulki / T-HSAB — Tunisian Hate Speech and Abusive Dataset	Only rows marked as non-hate-speech retained
10	Tunisian Reading Comprehension Dataset	QA dataset based on the Tunisian Constitution; 144 documents × 3 paragraphs × 3 QA pairs
11	Naim Mhedhbi — Tunisian Dialect Corpus v0	~40,000 Facebook comments/posts; only positive and neutral rows retained
12	TSAC — Tunisian Sentiment Analysis Corpus (paperswithcode)	~17,000 Facebook comments in Tunisian dialect
13	khaled123/Testtun	—
14	khaled123/Tuniset	—

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3. Intended Uses

3.1 Direct Use

This dataset is suitable for:

• Continual pretraining of Arabic or multilingual LLMs
• Domain adaptation for Tunisian dialect
• Text generation and understanding in Tunisian Arabic
• Corpus and linguistic analysis
• Data preparation for downstream NLP tasks

3.2 Out-of-Scope Use

This dataset is not intended for:

• High-stakes decision-making systems
• Surveillance or identity profiling
• Medical, legal, or financial applications without safeguards
• Claims of full representativeness of Tunisian dialects

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4. Dataset Statistics

Metric	Value
Total Tokens (GPT tokenization)	168,371,728

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5. Dataset Structure

The dataset is distributed in Parquet format and contains:

• text: Cleaned Tunisian Arabic text

Optional metadata fields may be included depending on preprocessing stages.

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6. Dataset Creation

The dataset is distributed in Parquet format and contains:

• text: Cleaned Tunisian Arabic text

Optional metadata fields may be included depending on preprocessing stages.

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6. Dataset Creation

6.1 Motivation

Tunisian Arabic is significantly underrepresented in open NLP resources. This dataset aims to:

• Provide a large-scale, clean corpus
• Enable reproducible research
• Improve dialectal Arabic model performance

6.2 Data Collection

The dataset is built by:

• Aggregating multiple public datasets
• Merging and standardizing formats
• Removing redundancy and inconsistencies

6.3 Processing Pipeline

The cleaning pipeline includes:

• Text normalization (whitespace, formatting)
• Removal of noisy artifacts (HTML tags, social media patterns)
• Emoji and symbol cleanup
• Filtering non-Arabic or mixed-script text
• Optional removal of digits and hashtags
• Duplicate and near-duplicate removal
• Minimum length and word count filtering
• Arabic-only filtering (final dataset)
• Data shuffling before export

6.4 Source Data Producers

Original data originates from contributors and maintainers of the upstream datasets. This dataset is a cleaned and merged derivative version.

6.5 Personal and Sensitive Information

As with many web-based corpora:

• Some personal or sensitive information may remain
• No guarantee of full anonymization is provided

Users should apply additional filtering if required for sensitive applications.

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7. Bias, Risks, and Limitations

• Source Bias: Reflects biases of original datasets and platforms
• Language Bias: Focus on Arabic script reduces code-switching diversity
• Coverage Limitation: Does not fully represent all Tunisian regions or sociolects

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8. Citation

8.1 This Dataset

BibTeX:

@dataset{tunisian_dialect_corpus_cleaned_2026,
  title     = {Tunisian Dialect Corpus (Cleaned Arabic-Only)},
  author    = {Syrinesmati},
  year      = {2026},
  publisher = {Hugging Face},
  url       = {https://huggingface.co/datasets/Syrinesmati/tunisian-dialect-corpus}
}

APA: Syrinesmati. (2026). Tunisian Dialect Corpus (Cleaned Arabic-Only) [Dataset]. Hugging Face. https://huggingface.co/datasets/Syrinesmati/tunisian-dialect-corpus

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8.2 Citations for Included Datasets

Tunisian Derja Dataset

@dataset{linagora2025LLM-tn,
  author = {Wajdi Ghezaiel and Jean-Pierre Lorré},
  title  = {Tunisian Derja Dataset},
  year   = {2025},
  month  = {January},
  url    = {https://huggingface.co/datasets/linagora/Tunisian_Derja_Dataset}
}

Tunisian-English Dialectic Derja

@dataset{Tunisian_English_dialectic_Derja,
  author = {Khaled Bouzaiene},
  title  = {Tunisian-English Dialectic Derja Dataset},
  year   = {2024},
  url    = {https://huggingface.co/datasets/khaled123/Tunisian_English_dialectic_Derja}
}

TunSwitch

@misc{abdallah2023leveraging,
  title         = {Leveraging Data Collection and Unsupervised Learning for Code-switched Tunisian Arabic Automatic Speech Recognition},
  author        = {Ahmed Amine Ben Abdallah and Ata Kabboudi and Amir Kanoun and Salah Zaiem},
  year          = {2023},
  eprint        = {2309.11327},
  archivePrefix = {arXiv},
  primaryClass  = {eess.AS}
}

LinTO Textual Dataset (Tunisian Arabic)

@misc{linagora2024Linto-tn,
  author       = {Hedi Naouara and Jérôme Louradour and Jean-Pierre Lorré},
  title        = {LinTO Audio and Textual Datasets to Train and Evaluate Automatic Speech Recognition in Tunisian Arabic Dialect},
  year         = {2024},
  month        = {October},
  note         = {Good Data Workshop, AAAI 2025},
  howpublished = {\url{https://huggingface.co/linagora/linto-asr-ar-tn-0.1}}
}

Arbi-Houssem STT/TTS Dataset

@dataset{arbi_houssem_stt_tts,
  author = {Arbi Houssem},
  title  = {Tunisian Dataset STT-TTS 15s Filtered Organised Mixed},
  url    = {https://huggingface.co/datasets/Arbi-Houssem/Tunisian_dataset_STT-TTS15s_filtred_organiser_Mixed}
}

LinTO ASR — Tunisian Arabic (linto-asr-ar-tn-0.1)

@misc{linagora2024linto_asr,
  author       = {Hedi Naouara and Jérôme Louradour and Jean-Pierre Lorré},
  title        = {LinTO ASR Tunisian Arabic Dialect Dataset},
  year         = {2024},
  howpublished = {\url{https://huggingface.co/datasets/linagora/linto-asr-ar-tn-0.1}}
}

Tunisian Arabic Dialects Identification (TADI)

@dataset{tadi,
  title = {Tunisian Arabic Dialects Identification (TADI)},
  note  = {Binary classification dataset for Tunisian vs. non-Tunisian Arabic dialect identification}
}

Tunisian Algerian Dialect (TAD) — TunBERT

@misc{tunbert_tad,
  author       = {InstaDeep},
  title        = {Tunisian Algerian Dialect Dataset},
  howpublished = {\url{https://github.com/instadeepai/tunbert}}
}

Tunninjaar — derja.ninja

@dataset{tunninjaar,
  author = {Khaled Bouzaiene},
  title  = {Tunninjaar},
  url    = {https://huggingface.co/datasets/khaled123/tunninjaar}
}

T-HSAB — Tunisian Hate Speech and Abusive Dataset

@inproceedings{mulki2019tsab,
  author    = {Hala Mulki and Hatem Haddad and Chedi Bechikh Ali and Halima Alshabani},
  title     = {T-HSAB: A Tunisian Hate Speech and Abusive Language Dataset},
  booktitle = {Proceedings of the 7th International Conference on Arabic Language Processing},
  year      = {2019}
}

Tunisian Reading Comprehension Dataset

@dataset{tunisian_rc,
  title = {Tunisian Reading Comprehension Dataset},
  note  = {Question-Answering dataset based on the Tunisian constitution; 144 documents, 3 paragraphs each, 3 QA pairs per paragraph}
}

Naim Mhedhbi — Tunisian Dialect Corpus v0

@dataset{mhedhbi_tunisian_v0,
  author = {Naim Mhedhbi},
  title  = {Tunisian Dialect Corpus v0},
  note   = {~40,000 Facebook comments and posts labeled for sentiment}
}

TSAC — Tunisian Sentiment Analysis Corpus

@dataset{tsac,
  title        = {Tunisian Sentiment Analysis Corpus (TSAC)},
  note         = {~17,000 Facebook comments in Tunisian dialect},
  howpublished = {\url{https://paperswithcode.com/dataset/tsac}}
}

khaled123/Testtun

@dataset{testtun,
  author = {Khaled Bouzaiene},
  title  = {Testtun},
  url    = {https://huggingface.co/datasets/khaled123/Testtun}
}

khaled123/Tuniset

@dataset{tuniset,
  author = {Khaled Bouzaiene},
  title  = {Tuniset},
  url    = {https://huggingface.co/datasets/khaled123/Tuniset}
}

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9. Dataset Card Authors

Syrinesmati

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10. Contact

For questions, issues, or updates, please use the Hugging Face dataset repository discussion/issues page.