SEACrowd/wikimatrix

Tasks

• machine-translation

Citation text from the card

@inproceedings{schwenk-etal-2021-wikimatrix,
    title = "{W}iki{M}atrix: Mining 135{M} Parallel Sentences in 1620 Language Pairs from {W}ikipedia",
    author = "Schwenk, Holger  and
      Chaudhary, Vishrav  and
      Sun, Shuo  and
      Gong, Hongyu  and
      Guzm{'a}n, Francisco",
    editor = "Merlo, Paola  and
      Tiedemann, Jorg  and
      Tsarfaty, Reut",
    booktitle = "Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume",
    month = apr,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.eacl-main.115",
    doi = "10.18653/v1/2021.eacl-main.115",
    pages = "1351--1361",
    abstract = "We present an approach based on multilingual sentence embeddings to automatically extract parallel sentences from the content
    of Wikipedia articles in 96 languages, including several dialects or low-resource languages. We do not limit the extraction process to
    alignments with English, but we systematically consider all possible language pairs. In total, we are able to extract 135M parallel sentences
    for 16720 different language pairs, out of which only 34M are aligned with English. This corpus is freely available. To get an indication
    on the quality of the extracted bitexts, we train neural MT baseline systems on the mined data only for 1886 languages pairs, and evaluate
    them on the TED corpus, ac

All datasets marked Permissive or share-alike | JSON