license: other
language:
- khg
- khm
- mya
- tet
- tha
- vie
pretty_name: Glotstorybook
task_categories:
- self-supervised-pretraining
tags:
- self-supervised-pretraining
The GlotStoryBook dataset is a compilation of children's storybooks from the Global Storybooks project, encompassing 174 languages organized for machine translation tasks. It features rows containing the text segment (text number), the language code, and the file name, which corresponds to the specific book and story segment. This structure allows for the comparison of texts across different languages by matching file names and text numbers between rows.
Languages
khg, khm, mya, tet, tha, vie
Supported Tasks
Self Supervised Pretraining
Dataset Usage
Using datasets library
from datasets import load_dataset
dset = datasets.load_dataset("SEACrowd/glotstorybook", trust_remote_code=True)
Using seacrowd library
# Load the dataset using the default config
dset = sc.load_dataset("glotstorybook", schema="seacrowd")
# Check all available subsets (config names) of the dataset
print(sc.available_config_names("glotstorybook"))
# Load the dataset using a specific config
dset = sc.load_dataset_by_config_name(config_name="<config_name>")
More details on how to load the seacrowd library can be found here.
Dataset Homepage
https://huggingface.co/datasets/cis-lmu/GlotStoryBook
Dataset Version
Source: 1.0.0. SEACrowd: 2024.06.20.
Dataset License
Other License (others) | We do not own any of the text from which these data has been extracted. All the files are collected from the repository located at https://github.com/global-asp/. The source repository for each text and file is stored in the dataset. Each file in the dataset is associated with one license from the CC family. The licenses include 'CC BY', 'CC BY-NC', 'CC BY-NC-SA', 'CC-BY', 'CC-BY-NC', and 'Public Domain'. We also license the code, actual packaging and the metadata of these data under the cc0-1.0.
Citation
If you are using the Glotstorybook dataloader in your work, please cite the following:
@inproceedings{kargaran2023glotlid,
title = {{GlotLID: Language Identification for Low-Resource Languages}},
author = {Kargaran, Amir Hossein and Imani, Ayyoob and Yvon, Fran{\c{c}}ois and Sch{"u}tze, Hinrich},
year = 2023,
booktitle = {The 2023 Conference on Empirical Methods in Natural Language Processing},
url = {https://openreview.net/forum?id=dl4e3EBz5j}
}
@article{lovenia2024seacrowd,
title={SEACrowd: A Multilingual Multimodal Data Hub and Benchmark Suite for Southeast Asian Languages},
author={Holy Lovenia and Rahmad Mahendra and Salsabil Maulana Akbar and Lester James V. Miranda and Jennifer Santoso and Elyanah Aco and Akhdan Fadhilah and Jonibek Mansurov and Joseph Marvin Imperial and Onno P. Kampman and Joel Ruben Antony Moniz and Muhammad Ravi Shulthan Habibi and Frederikus Hudi and Railey Montalan and Ryan Ignatius and Joanito Agili Lopo and William Nixon and Börje F. Karlsson and James Jaya and Ryandito Diandaru and Yuze Gao and Patrick Amadeus and Bin Wang and Jan Christian Blaise Cruz and Chenxi Whitehouse and Ivan Halim Parmonangan and Maria Khelli and Wenyu Zhang and Lucky Susanto and Reynard Adha Ryanda and Sonny Lazuardi Hermawan and Dan John Velasco and Muhammad Dehan Al Kautsar and Willy Fitra Hendria and Yasmin Moslem and Noah Flynn and Muhammad Farid Adilazuarda and Haochen Li and Johanes Lee and R. Damanhuri and Shuo Sun and Muhammad Reza Qorib and Amirbek Djanibekov and Wei Qi Leong and Quyet V. Do and Niklas Muennighoff and Tanrada Pansuwan and Ilham Firdausi Putra and Yan Xu and Ngee Chia Tai and Ayu Purwarianti and Sebastian Ruder and William Tjhi and Peerat Limkonchotiwat and Alham Fikri Aji and Sedrick Keh and Genta Indra Winata and Ruochen Zhang and Fajri Koto and Zheng-Xin Yong and Samuel Cahyawijaya},
year={2024},
eprint={2406.10118},
journal={arXiv preprint arXiv: 2406.10118}
}