Upload README.md with huggingface_hub

README.md

@@ -1,3 +1,184 @@
----
-license: cc-by-nc-4.0
----
+---
+language:
+- ha
+task_categories:
+- text-to-speech
+size_categories:
+- 1K<n<10K
+configs:
+- config_name: default
+  data_files:
+  - split: train
+    path: data/train-*
+dataset_info:
+  features:
+  - name: audio
+    dtype: audio
+  - name: text
+    dtype: string
+  - name: speaker_id
+    dtype: string
+  splits:
+  - name: train
+    num_examples: 1283
+---
+
+# Hausa TTS Dataset (HausaTTSEmbed)
+
+This dataset contains **1,283 Hausa language audio recordings** with transcriptions for Text-to-Speech (TTS) model training.
+
+## Dataset Details
+
+- **Language:** Hausa (ha)
+- **Total Samples:** 1,283
+- **Speakers:** 3 unique speakers
+- **Audio Format:** WAV files
+- **Sample Rate:** Original recordings (will be resampled to 24kHz during training)
+- **Text Length:** 4-141 characters (average: 24 characters)
+
+## Dataset Structure
+
+Each example contains:
+
+- **audio**: Audio file in WAV format
+- **text**: Hausa transcription with proper diacritics (e.g., "Ansamu ɓaraka acikin shirin")
+- **speaker_id**: UUID of the speaker (3 unique values)
+
+### Data Fields
+
+```python
+{
+    'audio': {
+        'path': str,      # Path to audio file
+        'array': ndarray, # Audio waveform
+        'sampling_rate': int
+    },
+    'text': str,          # Hausa transcription
+    'speaker_id': str     # Speaker identifier
+}
+```
+
+## Usage
+
+### Basic Loading
+
+```python
+from datasets import load_dataset
+
+dataset = load_dataset("Aybee5/HausaTTSEmbed", split="train")
+print(f"Loaded {len(dataset)} samples")
+
+# Access first sample
+sample = dataset[0]
+print(f"Text: {sample['text']}")
+print(f"Audio shape: {sample['audio']['array'].shape}")
+```
+
+### For Unsloth TTS Training
+
+This dataset is optimized for Unsloth TTS training:
+
+```python
+from datasets import load_dataset, Audio
+
+# Load dataset
+raw_ds = load_dataset("Aybee5/HausaTTSEmbed", split="train")
+
+# Speaker handling (Unsloth code)
+speaker_key = "source"
+if "source" not in raw_ds.column_names and "speaker_id" not in raw_ds.column_names:
+    print("Unsloth: No speaker found, adding default source")
+    new_column = ["0"] * len(raw_ds)
+    raw_ds = raw_ds.add_column("source", new_column)
+elif "source" not in raw_ds.column_names and "speaker_id" in raw_ds.column_names:
+    speaker_key = "speaker_id"
+
+# Resample to target sample rate
+target_sampling_rate = 24000
+raw_ds = raw_ds.cast_column("audio", Audio(sampling_rate=target_sampling_rate))
+
+# Optional: Split into train/validation
+split_ds = raw_ds.train_test_split(test_size=0.1, seed=42)
+train_ds = split_ds['train']
+val_ds = split_ds['test']
+
+print(f"Train: {len(train_ds)}, Validation: {len(val_ds)}")
+```
+
+### With Transformers
+
+```python
+from transformers import AutoProcessor
+
+processor = AutoProcessor.from_pretrained("your-tts-model")
+
+def preprocess_function(examples):
+    audio_arrays = [x["array"] for x in examples["audio"]]
+    
+    inputs = processor(
+        text=examples["text"],
+        audio=audio_arrays,
+        sampling_rate=24000,
+        return_tensors="pt",
+        padding=True
+    )
+    
+    return inputs
+
+# Apply preprocessing
+processed_ds = dataset.map(
+    preprocess_function,
+    batched=True,
+    remove_columns=dataset.column_names
+)
+```
+
+## Dataset Statistics
+
+- **Total Samples:** 1,283
+- **Unique Speakers:** 3
+- **Text Statistics:**
+  - Average length: 24.0 characters
+  - Min length: 4 characters
+  - Max length: 141 characters
+  - Language: Hausa with proper Unicode diacritics
+
+## Data Source
+
+This dataset was created using Mimic Studio recordings for Hausa language TTS development.
+
+## Intended Use
+
+This dataset is intended for:
+- Training Hausa Text-to-Speech models
+- Fine-tuning multilingual TTS models on Hausa
+- Research in low-resource language TTS
+- Multi-speaker TTS model development
+
+## Limitations
+
+- Limited to 3 speakers (may affect speaker diversity in trained models)
+- Relatively small dataset size (1,283 samples)
+- Audio quality depends on recording conditions
+
+## Citation
+
+If you use this dataset, please cite:
+
+```bibtex
+@dataset{hausa_tts_embed,
+  author = {Aybee5},
+  title = {Hausa TTS Dataset (HausaTTSEmbed)},
+  year = {2025},
+  publisher = {Hugging Face},
+  url = {https://huggingface.co/datasets/Aybee5/HausaTTSEmbed}
+}
+```
+
+## License
+
+Please specify your license here.
+
+## Contact
+
+For questions or issues regarding this dataset, please open an issue in the dataset repository.