Update README.md

README.md

@@ -1,40 +1,163 @@
----
-dataset_info:
-  features:
-  - name: audio
-    dtype:
-      audio:
-        sampling_rate: 16000
-  - name: sentence
-    dtype: string
-  splits:
-  - name: train
-    num_bytes: 15358706439
-    num_examples: 94587
-  - name: validation
-    num_bytes: 853288011
-    num_examples: 5255
-  - name: test
-    num_bytes: 853288447
-    num_examples: 5255
-  download_size: 16777443696
-  dataset_size: 17065282897
-configs:
-- config_name: default
-  data_files:
-  - split: train
-    path: data/train-*
-  - split: validation
-    path: data/validation-*
-  - split: test
-    path: data/test-*
-language:
-- ar
-tags:
-- STT
-- Wisper
-- EGY_DATASET
-- Finetuning
-size_categories:
-- 100K<n<1M
----
+---
+language:
+- ar
+task_categories:
+- automatic-speech-recognition
+tags:
+- whisper
+- arabic
+- dialect
+- speech
+- asr
+pretty_name: Arabic Whisper Multi-Dialect Dataset
+size_categories:
+- 100K<n<1M
+---
+
+# Arabic Whisper Multi-Dialect ASR Dataset
+
+A comprehensive multi-dialect Arabic speech recognition dataset prepared for Whisper model fine-tuning.
+
+## Dataset Description
+
+This dataset combines high-quality Arabic speech data from multiple dialects, specifically curated for fine-tuning OpenAI's Whisper models on Arabic speech recognition tasks.
+
+### Dialects Included
+
+- **Modern Standard Arabic (MSA)** - Formal Arabic used in media and formal contexts
+- **Egyptian Arabic (EGY)** - The most widely understood Arabic dialect
+- **Gulf Arabic (GULF)** - Arabic dialects from the Gulf region
+
+### Dataset Statistics
+
+- **Total Samples**: ~105,000 audio-text pairs
+- **Train Split**: ~94,500 samples (90%)
+- **Validation Split**: ~5,250 samples (5%)
+- **Test Split**: ~5,250 samples (5%)
+- **Audio Format**: 16kHz, mono
+- **Text**: Normalized Arabic script
+
+### Source Datasets
+
+This dataset is a combination of the following sources:
+
+1. **MightyStudent/Egyptian-ASR-MGB-3** - Egyptian dialect broadcast data
+2. **MAdel121/arabic-egy-cleaned** - Cleaned Egyptian Arabic speech
+3. **Nourhann/filtered_common_voices_16khz** - Modern Standard Arabic
+4. **badrex/arabic-speech-SADA22-Khaliji** - Gulf dialect speech (30% sample)
+
+## Dataset Structure
+```python
+DatasetDict({
+    train: Dataset({
+        features: ['audio', 'sentence'],
+        num_rows: ~94500
+    })
+    validation: Dataset({
+        features: ['audio', 'sentence'],
+        num_rows: ~5250
+    })
+    test: Dataset({
+        features: ['audio', 'sentence'],
+        num_rows: ~5250
+    })
+})
+```
+
+### Data Fields
+
+- `audio`: Audio file (16kHz sampling rate)
+- `sentence`: Transcription text in Arabic
+- `dialect`: Dialect label ('msa', 'egy', or 'gulf')
+
+## Usage
+
+### Loading the Dataset
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("MadLook/arabic-whisper-multidialect")
+
+print(dataset)
+# Access splits
+train_data = dataset['train']
+val_data = dataset['validation']
+test_data = dataset['test']
+```
+
+### Fine-tuning Whisper
+```python
+from transformers import WhisperProcessor, WhisperForConditionalGeneration
+
+# Load model and processor
+processor = WhisperProcessor.from_pretrained("openai/whisper-small", language="Arabic", task="transcribe")
+model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small")
+
+# Prepare dataset
+def prepare_dataset(batch):
+    audio = batch["audio"]
+    batch["input_features"] = processor.feature_extractor(audio["array"], sampling_rate=audio["sampling_rate"]).input_features[0]
+    batch["labels"] = processor.tokenizer(batch["sentence"]).input_ids
+    return batch
+
+dataset = dataset.map(prepare_dataset)
+
+# Continue with training...
+```
+
+## Data Processing
+
+The dataset has been processed with the following steps:
+
+1. **Audio normalization**: All audio resampled to 16kHz mono
+2. **Text normalization**: Arabic text normalized (diacritics removed, Alef forms unified)
+3. **Dialect balancing**: Datasets sampled to ensure balanced representation
+4. **Quality filtering**: Low-quality samples removed
+5. **Train/Val/Test split**: 90/5/5 split with shuffling
+
+## Intended Use
+
+### Primary Use Cases
+
+- Fine-tuning Whisper models for Arabic ASR
+- Multi-dialect Arabic speech recognition research
+- Arabic speech technology development
+- Dialect-aware speech recognition systems
+
+### Considerations
+
+- This dataset combines multiple dialects; consider dialect-specific fine-tuning if needed
+- Text is normalized and may not preserve dialectal spelling variations
+- Dataset is balanced across dialects but individual dialect performance may vary
+
+## Limitations
+
+- Gulf dialect representation is lower (30% of original dataset)
+- No code-switching samples included
+- Limited to broadcast and read speech domains
+- May not generalize well to conversational or noisy speech
+
+## Citation
+
+If you use this dataset, please cite the original source datasets:
+```bibtex
+@dataset{arabic_whisper_multidialect,
+  title={Arabic Whisper Multi-Dialect Dataset},
+  author={MadLook},
+  year={2025},
+  publisher={Hugging Face},
+  howpublished={\url{https://huggingface.co/datasets/MadLook/arabic-whisper-multidialect}}
+}
+```
+
+## License
+
+This dataset combines data from multiple sources. Please refer to the original datasets for their respective licenses:
+- MightyStudent/Egyptian-ASR-MGB-3
+- MAdel121/arabic-egy-cleaned
+- Nourhann/filtered_common_voices_16khz
+- badrex/arabic-speech-SADA22-Khaliji
+
+## Acknowledgments
+
+This dataset builds upon the excellent work of the Arabic NLP and speech recognition community. Special thanks to the creators of the source datasets for making their data publicly available.