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--- |
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dataset_info: |
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features: |
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- name: audio |
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dtype: |
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audio: |
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sampling_rate: 16000 |
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- name: sentence |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 131539467.61728086 |
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num_examples: 5346 |
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- name: test |
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num_bytes: 32351673.510719135 |
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num_examples: 1337 |
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download_size: 163256695 |
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dataset_size: 163891141.128 |
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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: test |
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path: data/test-* |
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--- |
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# Urban Bus Wolof Speech Dataset |
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This dataset contains audio recordings and their transcriptions in Wolof, related to urban bus transportation. The goal is to facilitate the development of Automatic Speech Recognition (ASR) models to help illiterate people use existing apps to find which bus they can take to reach their destination without needing to know how to read or write. |
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## Dataset Description |
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- **Language**: Wolof (`wo`) |
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- **Domain**: Urban transportation |
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- **Data Type**: Audio recordings and transcriptions |
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- **Audio File Format**: MP3 |
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- **Sampling Rate**: 16 kHz |
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- **Total Examples**: 6,683 |
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- **Training Set**: 5,346 examples (80%) |
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- **Test Set**: 1,337 examples (20%) |
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## Dataset Structure |
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### Features |
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- `audio`: An audio file containing the speech in Wolof. |
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- **Format**: MP3 |
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- **Sampling Rate**: 16 kHz |
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- `sentence`: The textual transcription of the audio in Wolof. |
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### Splits |
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The dataset is divided into two splits: |
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| Split | Number of Examples | |
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|--------|---------------------| |
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| Train | 5,346 | |
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| Test | 1,337 | |
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## Example Usage |
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Here's how to load and use this dataset with the 🤗 Datasets library: |
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```python |
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from datasets import load_dataset |
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# Load the dataset |
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dataset = load_dataset("vonewman/urban-bus-wolof") |
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# Access an example from the 'train' split |
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print(dataset['train'][0]) |
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# Expected output: |
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# { |
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# 'audio': { |
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# 'path': '.../train/audio/<audio_file>.mp3', |
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# 'array': array([...]), |
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# 'sampling_rate': 16000 |
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# }, |
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# 'sentence': 'Transcription of the audio in Wolof' |
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# } |
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