| | --- |
| | language: |
| | - en |
| | - pcm |
| | task_categories: |
| | - automatic-speech-recognition |
| | - text-generation |
| | tags: |
| | - whisper |
| | - nigerian-pidgin |
| | - speech-recognition |
| | - text |
| | size_categories: |
| | - 1K<n<10K |
| | --- |
| | |
| | # Nigerian Pidgin Audio + Text Dataset for Whisper Fine-tuning |
| |
|
| | Nigerian Pidgin speech dataset for Whisper fine-tuning |
| |
|
| | ## Dataset Summary |
| |
|
| | This dataset contains audio recordings and transcriptions in Nigerian Pidgin English, designed for fine-tuning speech recognition models, particularly OpenAI's Whisper. |
| |
|
| | ## Dataset Structure |
| |
|
| | - **Train Split**: 65 samples |
| | - **Test Split**: 8 samples |
| | - **Total Duration**: 0.0 hours (estimated) |
| | - **Average Duration**: 2.4 seconds per sample |
| | - **Sample Rate**: 16kHz |
| | - **Audio Format**: WAV |
| |
|
| | ## Sample Data |
| |
|
| | Here are some example transcriptions from the dataset: |
| |
|
| | ``` |
| | - ♪ EVERYDAY NA BILLING ♪ |
| | - ♪ SHE CALL ME SANTA ♪ |
| | - ♪ SEYCHELLES, ADDIS ABABA ♪ |
| | - ♪ I FOR DON TURN VISITOR ♪ |
| | - ♪ SHE NO WAN TURN TO OROBOKIBO ♪ |
| | ``` |
| |
|
| | ## Usage |
| |
|
| | ### Loading the Dataset |
| |
|
| | ```python |
| | from datasets import load_dataset |
| | |
| | # Load the dataset |
| | dataset = load_dataset("Rexe/nigerian-pidgin-speech") |
| | |
| | # Access train and test splits |
| | train_data = dataset["train"] |
| | test_data = dataset["test"] |
| | ``` |
| |
|
| | ### Training with Transformers |
| |
|
| | ```python |
| | from transformers import WhisperForConditionalGeneration, WhisperProcessor |
| | |
| | # Load model and processor |
| | model = WhisperForConditionalGeneration.from_pretrained("openai/whisper-small") |
| | processor = WhisperProcessor.from_pretrained("openai/whisper-small") |
| | |
| | # Your training code here... |
| | ``` |
| |
|
| | ## Google Colab Training |
| |
|
| | Use this dataset directly in Google Colab for training: |
| |
|
| | ```python |
| | # Install requirements |
| | !pip install datasets transformers torch torchaudio |
| | |
| | # Load dataset |
| | from datasets import load_dataset |
| | dataset = load_dataset("Rexe/nigerian-pidgin-speech") |
| | |
| | # Start training... |
| | ``` |
| |
|
| | ## Languages |
| |
|
| | - **English** (en): Base language |
| | - **Nigerian Pidgin** (pcm): Target language for fine-tuning |
| |
|
| | ## Common Pidgin Phrases |
| |
|
| | - "How you dey?" - How are you? |
| | - "I dey fine o" - I am fine |
| | - "Wetin dey happen?" - What's happening? |
| | - "Make we go" - Let's go |
| | - "Abeg help me" - Please help me |
| |
|
| |
|
| | ## Citation |
| |
|
| | If you use this dataset, please cite: |
| |
|
| | ```bibtex |
| | @dataset{nigerian_pidgin_speech, |
| | title={Nigerian Pidgin Audio + Text Dataset}, |
| | author={Your Name}, |
| | year={2024}, |
| | url={https://huggingface.co/datasets/Rexe/nigerian-pidgin-speech} |
| | } |
| | ``` |
| |
|
| | ## License |
| |
|
| | This dataset is released under the MIT License. |
| |
|