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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: a novel large-scale Vietnamese speech corpus (LSVSC) |
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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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- name: topic |
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dtype: string |
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- name: gender |
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dtype: string |
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- name: dialect |
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dtype: string |
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- name: emotion |
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dtype: string |
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- name: age |
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dtype: string |
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splits: |
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- name: train |
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num_bytes: 8620435812.644 |
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num_examples: 45458 |
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- name: validation |
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num_bytes: 1102706521.852 |
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num_examples: 5682 |
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- name: test |
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num_bytes: 1136311929.744 |
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num_examples: 5683 |
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download_size: 11575801683 |
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dataset_size: 10859454264.239998 |
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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: validation |
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path: data/validation-* |
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- split: test |
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path: data/test-* |
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--- |
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# unofficial mirror of LSVSC dataset (novel large-scale Vietnamese speech corpus) |
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official announcement: https://www.mdpi.com/2079-9292/13/5/977 |
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official download: https://drive.google.com/drive/folders/1tiPKaIOC7bt6isv5qFqf61O_2jFK8ZOI |
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100h, 57k samples |
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pre-process: remove non-sense characters: `\r` `\n` |
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need to do: check misspelling, restore foreign words phonetised to vietnamese |
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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/LSVSC", 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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``` |
