README.md

---
language:
- ar
- arz
- acm
- apc
- ary
- arb
language_bcp47:
- ar-EG
- ar-IQ
- ar-LB
- ar-MA
- ar-SA
license: mit
tags:
- arabic
- dialects
- nlp
- speech-to-text
- transcription
- text-classification
- linguistics
- corpus
- egyptian
- gulf
- levantine
- maghrebi
- iraqi
- cl100k_base
task_categories:
- text-generation
- text-classification
pretty_name: Arabic Dialect Corpus
size_categories:
- 100K<n<1M
configs:
- config_name: classified
  data_files:
  - split: train
    path: classified/train-*
- config_name: default
  data_files:
  - split: train
    path: data/train-*
dataset_info:
- config_name: classified
  features:
  - name: text
    dtype: string
  - name: utterance_type
    dtype: string
  - name: dialect
    dtype: string
  - name: tokens
    dtype: int64
  - name: topic
    dtype: string
  - name: topic_confidence
    dtype: float64
  splits:
  - name: train
    num_bytes: 3096333
    num_examples: 10000
  download_size: 1531863
  dataset_size: 3096333
- config_name: default
  features:
  - name: text
    dtype: string
  - name: utterance_type
    dtype: string
  - name: dialect
    dtype: string
  - name: tokens
    dtype: int64
  splits:
  - name: train
    num_bytes: 61592976
    num_examples: 211593
  download_size: 26183021
  dataset_size: 61592976
---

# Arabic Dialect Corpus

A comprehensive collection of Arabic dialectal text, standardized for Natural Language Processing (NLP) model training, evaluation, and linguistic analysis. This corpus has been meticulously processed to ensure high-quality tokenization and consistent metadata.

## Dataset Statistics

| Metric | Value |
| :--- | :--- |
| **Total Records** | 127,180 |
| **Total Tokens** | 5,802,324 |
| **Average Tokens per Record** | 45.62 |
| **Dialect Categories** | 5 |

## Changelog

### Version 1.0 (January 2026)

This release establishes the baseline for the corpus with strict quality controls:

- **Token Count**: Validated 5.8M+ tokens using `cl100k_base` (GPT-4 standard).
- **Data Density**: Optimized average record length to ~45 tokens for efficient training.
- **Dialect Coverage**: Confirmed distribution across 5 distinct dialect categories.
- **Quality Assurance**: Zero empty records and standardized metadata schema.

## Dataset Structure

Each record in the dataset contains the following fields:

- `text` (string): The raw Arabic text content.
- `topic` (string): The semantic category or topic of the text.
- `utterance_type` (string): Classification of the utterance (e.g., statement, question).
- `dialect` (string): The regional dialect name: `Masri` (Egyptian), `Khaleeji` (Gulf), `Levantine`, `Maghrebi` (North African), or `Iraqi`.
- `tokens` (int): The precise token count calculated using `cl100k_base` encoding.

## Usage

### Loading the Dataset

The dataset is hosted on the Hugging Face Hub and can be loaded directly using the `datasets` library.

```python
from datasets import load_dataset

# Load the complete dataset
dataset = load_dataset("dataflare/arabic-dialect-corpus")
```

## Detailed Methodology

### Collection and Processing
The data was aggregated from diverse sources including transcribed media and public archives. The processing pipeline involved:
1.  **Normalization**: Text normalization to remove noise while preserving dialectal features.
2.  **Segmentation**: Splitting long passages into training-ready chunks.
3.  **Token Counting**: Rigorous token counting using `tiktoken` to assist in curriculum training and length bucketing.

## Citation and License

This dataset is released under the **MIT License**.

If you rely on this corpus for your research or application, please cite it using the following BibTeX entry:

```bibtex
@dataset{arabic_dialect_corpus,
  title={Arabic Dialect Corpus},
  author={Dataflare},
  year={2026},
  publisher={Hugging Face},
  url={https://huggingface.co/datasets/dataflare/arabic-dialect-corpus}
}
```