Datasetpublic

doof-ferb/infore2_audiobooks

unofficial mirror of InfoRe Technology public dataset №2 official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/ 415h, 315k samples, vietnamese audiobooks of chinese wǔxiá 武俠 & xiānxiá 仙俠 bộ dữ liệu bóc ra từ YouTube đọc truyện võ hiệp & tiên hiệp, áp dụng kĩ thuật đối chiếu văn bản để dán nhãn tự động official download:… See the full description on the dataset page: https://huggingface.co/datasets/doof-ferb/infore2_audiobooks.

sourceHugging Facecc-by-4.0updated 3y agoView on Hugging Face

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Dataset Card

unofficial mirror of InfoRe Technology public dataset №2

official announcement: https://www.facebook.com/groups/j2team.community/permalink/1010834009248719/

415h, 315k samples, vietnamese audiobooks of chinese wǔxiá 武俠 & xiānxiá 仙俠

bộ dữ liệu bóc ra từ YouTube đọc truyện võ hiệp & tiên hiệp, áp dụng kĩ thuật đối chiếu văn bản để dán nhãn tự động

official download: magnet:?xt=urn:btih:41f1290325ecb6f1230ecdff2441527c9cd43fd0&dn=audiobooks.zip&tr=http%3A%2F%2Foffice.socials.vn%3A8725%2Fannounce

mirror: https://files.huylenguyen.com/audiobooks.zip

unzip password: BroughtToYouByInfoRe

pre-process: none

need to do: check misspelling

usage with HuggingFace:

python

# pip install -q "datasets[audio]"
from datasets import load_dataset
from torch.utils.data import DataLoader

dataset = load_dataset("doof-ferb/infore2_audiobooks", split="train", streaming=True)
dataset.set_format(type="torch", columns=["audio", "transcription"])
dataloader = DataLoader(dataset, batch_size=4)