--- dataset_info: features: - name: vocalized dtype: string - name: erroneous dtype: string splits: - name: train num_bytes: 4494447826 num_examples: 1460625 - name: valid num_bytes: 93024950 num_examples: 30129 - name: test num_bytes: 46293622 num_examples: 15062 download_size: 2248929902 dataset_size: 4633766398 configs: - config_name: default data_files: - split: train path: data/train-* - split: valid path: data/valid-* - split: test path: data/test-* license: mit task_categories: - text2text-generation language: - ar tags: - Speech-Correction - Diacritics - Vocalized - Arabic - Tashkeel --- # **Text with Diacritics Correction Dataset** [![Hugging Face](https://img.shields.io/badge/Hugging%20Face-Dataset-yellow)](https://huggingface.co/datasets/FlouBsy/Text-with-Diacritics-Correction) ## **Overview** 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**. ### **Key Features** ✅ **Preprocessed Arabic text**: Cleaned `vocalized` column by removing non-Arabic characters, symbols, emojis, brackets, and numbers. ✅ **Injected realistic errors**: Includes four types of errors that simulate real-world **speech and typing mistakes**. ✅ **Large-scale dataset**: Over **1.5 million** text samples for robust training. ✅ **Suitable for NLP tasks**: Useful for **text correction, speech recognition, and Arabic NLP research**. --- ## **Dataset Details** ### **Statistics** | Split | Samples | |------------|---------:| | Train | 1,460,625 | | Validation | 30,129 | | Test | 15,062 | | **Total** | **1,505,816** | ### **Data Format** - **File Type**: Parquet - **Columns**: - `vocalized`: Preprocessed Arabic text - `erroneous`: The same text with injected errors --- ## **Error Injection Details** We introduced **four types of common Arabic text errors** to enhance the dataset’s usability for speech and typing correction: 1. **Keyboard Errors** 🖥️ - Mistyped letters based on nearby keyboard keys. - Example: `السلام` → `الستام` (minor keyboard slip). 2. **Ordering Errors** 🔀 - Swapped adjacent letters. - Example: `مرحبا` → `مرحاب` (common typing mistake). 3. **Phonetic Errors** 🎙️ - Replaced letters with phonetically similar ones. - Example: `ن` ↔ `م`, `س` ↔ `ث`. 4. **Diacritic Errors** 🐪 - Altered or removed Arabic diacritics (`Tashkeel`). - Example: `كَتَبَ` → `كَتُبَ`. These errors mimic **real-world mistakes** in **speech recognition and Arabic typing**, improving model robustness. --- ## **Usage** ### **Loading the Dataset in Python** ```python from datasets import load_dataset dataset = load_dataset("FlouBsy/Text-with-Diacritics-Correction") # Example access print(dataset['train'][0]) # Show first sample ``` ## Collaborators - **[Basma M.](https://huggingface.co/FlouBsy)** (Main Contributor) - **[Selsabeel A.](https://huggingface.co/Selsabeel)** ## Citations ``` @misc{arabic_tashkeel_dataset, author = {Abdou}, title = {{Arabic Tashkeel Dataset}}, year = {2024}, url = {https://huggingface.co/datasets/Abdou/arabic-tashkeel-dataset} } @misc{Text-with-Diacritics-Correction, author = {Basma M., Selsabeel A.}, title = {{Arabic Speech & Typing Errors with Diacritics Dataset}}, year = {2025}, url = {https://huggingface.co/datasets/FlouBsy/Text-with-Diacritics-Correction} } ```