Basma
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README.md
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---
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dataset_info:
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features:
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- name: vocalized
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dtype: string
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- name: erroneous
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dtype: string
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splits:
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- name: train
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num_bytes: 4494954114
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num_examples: 1463790
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- name: valid
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num_bytes: 93033856
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num_examples: 30181
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- name: test
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num_bytes: 46297886
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num_examples: 15091
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download_size: 2248412824
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dataset_size: 4634285856
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: valid
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path: data/valid-*
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- split: test
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path: data/test-*
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license: mit
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task_categories:
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- text2text-generation
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language:
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- ar
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tags:
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- Speech-Correction
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- Diacritics
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- Vocalized
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- Arabic
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- Tashkeel
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---
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---
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dataset_info:
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features:
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- name: vocalized
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dtype: string
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- name: erroneous
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dtype: string
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splits:
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- name: train
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num_bytes: 4494954114
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num_examples: 1463790
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- name: valid
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num_bytes: 93033856
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num_examples: 30181
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+
- name: test
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num_bytes: 46297886
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num_examples: 15091
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download_size: 2248412824
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dataset_size: 4634285856
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configs:
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- config_name: default
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data_files:
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- split: train
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path: data/train-*
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- split: valid
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path: data/valid-*
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- split: test
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path: data/test-*
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license: mit
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task_categories:
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- text2text-generation
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language:
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- ar
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tags:
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- Speech-Correction
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- Diacritics
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- Vocalized
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- Arabic
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- Tashkeel
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---
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# **Text with Diacritics Correction Dataset**
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[](https://huggingface.co/datasets/FlouBsy/Text-with-Diacritics-Correction)
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## **Overview**
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This dataset is an **Arabic dataset** derived from [Abdou/arabic-tashkeel-dataset](https://huggingface.co/datasets/Abdou/arabic-tashkeel-dataset), with additional **preprocessing and error injection** to help train models for **speech and typing correction**.
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### **Key Features**
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✅ **Preprocessed Arabic text**: Cleaned `vocalized` column by removing non-Arabic characters, symbols, emojis, brackets, and numbers.
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✅ **Injected realistic errors**: Includes four types of errors that simulate real-world **speech and typing mistakes**.
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✅ **Large-scale dataset**: Over **1.5 million** text samples for robust training.
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✅ **Suitable for NLP tasks**: Useful for **text correction, speech recognition, and Arabic NLP research**.
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---
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## **Dataset Details**
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### **Statistics**
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| Split | Samples |
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|------------|---------:|
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| Train | 1,463,790 |
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| Validation | 30,181 |
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| Test | 15,091 |
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| **Total** | **1,509,062** |
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### **Data Format**
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- **File Type**: Parquet
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- **Columns**:
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- `vocalized`: Preprocessed Arabic text
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- `erroneous`: The same text with injected errors
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---
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## **Error Injection Details**
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We introduced **four types of common Arabic text errors** to enhance the dataset’s usability for speech and typing correction:
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1. **Keyboard Errors** 🖥️
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- Mistyped letters based on nearby keyboard keys.
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- Example: `السلام` → `الستام` (minor keyboard slip).
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2. **Ordering Errors** 🔀
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- Swapped adjacent letters.
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- Example: `مرحبا` → `مرحاب` (common typing mistake).
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3. **Phonetic Errors** 🎙️
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- Replaced letters with phonetically similar ones.
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- Example: `ن` ↔ `م`, `س` ↔ `ث`.
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4. **Diacritic Errors** ٍّ ُٰ
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- Altered or removed Arabic diacritics (`Tashkeel`).
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- Example: `كَتَبَ` → `كَتُبَ`.
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These errors mimic **real-world mistakes** in **speech recognition and Arabic typing**, improving model robustness.
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---
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## **Usage**
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### **Loading the Dataset in Python**
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```python
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from datasets import load_dataset
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dataset = load_dataset("FlouBsy/Text-with-Diacritics-Correction")
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# Example access
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print(dataset['train'][0]) # Show first sample
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```
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## Collaborators
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- **[Basma M.](https://huggingface.co/FlouBsy)** (Main Contributor)
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- **[Selsabeel A.](https://huggingface.co/TheirUsernameHere)**
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## Citations
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@misc{arabic_tashkeel_dataset,
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author = {[Original Dataset Author](https://huggingface.co/Abdou)},
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title = {Arabic Tashkeel Dataset},
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year = {2024},
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url = {https://huggingface.co/datasets/Abdou/arabic-tashkeel-dataset}
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}
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@misc{Text-with-Diacritics-Correction,
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author = {Basma M., Selsabeel A.},
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title = {Arabic Speech & Typing Errors with Diacritics Dataset},
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year = {2025},
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url = {https://huggingface.co/datasets/FlouBsy/Text-with-Diacritics-Correction}
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}
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