Datasets:
metadata
task_categories:
- translation
language:
- af
- am
- ar
- as
- az
- be
- bg
- bn
- br
- bs
- ca
- cs
- cy
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fy
- ga
- gd
- gl
- ha
- he
- hi
- hr
- hu
- hy
- id
- is
- it
- ja
- jv
- ka
- kk
- km
- kn
- ko
- ku
- ky
- la
- lo
- lt
- mg
- mk
- ml
- mn
- mr
- ms
- my
- ne
- nl
- 'no'
- om
- or
- pa
- pl
- ps
- pt
- ro
- ru
- sa
- sd
- si
- sk
- sl
- so
- sq
- sr
- su
- sv
- sw
- ta
- te
- th
- tl
- tr
- ug
- uk
- ur
- uz
- vi
- xh
- yi
- zh
Collection of OPUS
Corpus from https://opus.nlpl.eu has been collected. The following corpora have been included:
25,000 samples (randomly sampled within the first 100,000 samples) per language pair of each corpus were collected, with no modification of data.
Licenses
OPUS
@inproceedings{tiedemann2012parallel,
title={Parallel data, tools and interfaces in OPUS.},
author={Tiedemann, J{\"o}rg},
booktitle={Lrec},
volume={2012},
pages={2214--2218},
year={2012},
organization={Citeseer}
}
Tatoeba
CC BY 2.0 FR
TED2020
CC BY–NC–ND 4.0
@inproceedings{reimers-2020-multilingual-sentence-bert,
title = "Making Monolingual Sentence Embeddings Multilingual using Knowledge Distillation",
author = "Reimers, Nils and Gurevych, Iryna",
booktitle = "Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing",
month = "11",
year = "2020",
publisher = "Association for Computational Linguistics",
url = "https://arxiv.org/abs/2004.09813",
}
WikiMatrix
CC-BY-SA 4.0
@article{schwenk2019wikimatrix,
title={Wikimatrix: Mining 135m parallel sentences in 1620 language pairs from wikipedia},
author={Schwenk, Holger and Chaudhary, Vishrav and Sun, Shuo and Gong, Hongyu and Guzm{\'a}n, Francisco},
journal={arXiv preprint arXiv:1907.05791},
year={2019}
}
UNPC
@inproceedings{ziemski2016united,
title={The united nations parallel corpus v1. 0},
author={Ziemski, Micha{\l} and Junczys-Dowmunt, Marcin and Pouliquen, Bruno},
booktitle={Proceedings of the Tenth International Conference on Language Resources and Evaluation (LREC'16)},
pages={3530--3534},
year={2016}
}