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--- |
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license: cc-by-4.0 |
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task_categories: |
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- automatic-speech-recognition |
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- text-to-speech |
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language: |
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- vi |
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pretty_name: InfoRe Technology public dataset №1 |
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size_categories: |
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- 10K<n<100K |
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dataset_info: |
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features: |
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- name: audio |
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dtype: audio |
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- name: transcription |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 7370428827.92 |
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num_examples: 14935 |
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download_size: 7832947140 |
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dataset_size: 7370428827.92 |
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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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--- |
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# unofficial mirror of InfoRe Technology public dataset №1 |
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official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/ |
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25h, 14.9k samples, InfoRe paid a contractor to read text |
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official download: `magnet:?xt=urn:btih:1cbe13fb14a390c852c016a924b4a5e879d85f41&dn=25hours.zip&tr=http%3A%2F%2Foffice.socials.vn%3A8725%2Fannounce` |
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mirror: https://files.huylenguyen.com/25hours.zip |
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unzip password: `BroughtToYouByInfoRe` |
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pre-process: none |
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need to do: check misspelling |
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usage with HuggingFace: |
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```python |
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# pip install -q "datasets[audio]" |
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from datasets import load_dataset |
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from torch.utils.data import DataLoader |
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dataset = load_dataset("doof-ferb/infore1_25hours", split="train", streaming=True) |
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dataset.set_format(type="torch", columns=["audio", "transcription"]) |
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dataloader = DataLoader(dataset, batch_size=4) |
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``` |
