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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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  - split: train
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  path: data/train-*
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  ---
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
 
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  ---
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+ license: cc-by-nc-sa-4.0
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+ task_categories: ["automatic-speech-recognition", "text-to-speech"]
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+ language: ["vi"]
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+ pretty_name: FPT Open Speech Dataset (FOSD)
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+ size_categories: ["10K<n<100K"]
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  dataset_info:
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  features:
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  - name: audio
 
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  - split: train
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  path: data/train-*
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  ---
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+
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+ # unofficial mirror of FPT Open Speech Dataset (FOSD)
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+
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+ released publicly in 2018 by FPT Corporation
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+
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+ 100h, 26k samples
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+
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+ official link (dead): https://fpt.ai/fpt-open-speech-data/
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+ mirror: https://data.mendeley.com/datasets/k9sxg2twv4/4
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+
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+ DOI: `10.17632/k9sxg2twv4.4`
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+
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+ pre-process:
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+ - remove non-sense strings: `-N` `\r\n`
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+ - remove 4 files because missing transcription:
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+ - `Set001_V0.1_008210.mp3`
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+ - `Set001_V0.1_010753.mp3`
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+ - `Set001_V0.1_011477.mp3`
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+ - `Set001_V0.1_011841.mp3`
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+
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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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+
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+ dataset = load_dataset("doof-ferb/fpt_fosd", 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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+ ```