Datasets:
Tasks:
Translation
Multilinguality:
translation
Language Creators:
expert-generated
Annotations Creators:
crowdsourced
License:
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Dataset Description
Train, validation and test splits for TED talks as in http://phontron.com/data/ted_talks.tar.gz. Data is detokenized using moses.
Example of loading:
dataset = load_dataset("davidstap/ted_talks", "ar_en", trust_remote_code=True)
Note that ar_en
and en_ar
will result in the same data being loaded..
The following languages are available:
- ar
- az
- be
- bg
- bn
- bs
- cs
- da
- de
- el
- en
- eo
- es
- et
- eu
- fa
- fi
- fr
- fr-ca
- gl
- he
- hi
- hr
- hu
- hy
- id
- it
- ja
- ka
- kk
- ko
- ku
- lt
- mk
- mn
- mr
- ms
- my
- nb
- nl
- pl
- pt
- pt-br
- ro
- ru
- sk
- sl
- sq
- sr
- sv
- ta
- th
- tr
- uk
- ur
- vi
- zh
- zh-cn
- zh-tw
Citation Information
@inproceedings{qi-etal-2018-pre,
title = "When and Why Are Pre-Trained Word Embeddings Useful for Neural Machine Translation?",
author = "Qi, Ye and
Sachan, Devendra and
Felix, Matthieu and
Padmanabhan, Sarguna and
Neubig, Graham",
booktitle = "Proceedings of the 2018 Conference of the North {A}merican Chapter of the Association for Computational Linguistics: Human Language Technologies, Volume 2 (Short Papers)",
month = jun,
year = "2018",
address = "New Orleans, Louisiana",
publisher = "Association for Computational Linguistics",
url = "https://aclanthology.org/N18-2084",
doi = "10.18653/v1/N18-2084",
pages = "529--535",
}
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