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SEACrowd/ccmatrix

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The checks could not identify a recognised licence ID in the dataset's metadata.

Declared licence: bsd, from the tagEvidence: README.md at b7164d1
Licence files: LICENSE, licence not identifiedEvidence: LICENSE at b7164d1
Declared sources: None listed in the card metadata
Access gated on Hugging Face: No

Each cell links to what was checked: a file, a file list or a Hub record.

Tasks

machine-translation

Citation text from the card

@inproceedings{schwenk-etal-2021-ccmatrix,
    title = "{CCM}atrix: Mining Billions of High-Quality Parallel Sentences on the Web",
    author = "Schwenk, Holger  and
      Wenzek, Guillaume  and
      Edunov, Sergey  and
      Grave, Edouard  and
      Joulin, Armand  and
      Fan, Angela",
    editor = "Zong, Chengqing  and
      Xia, Fei  and
      Li, Wenjie  and
      Navigli, Roberto",
    booktitle = "Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers)",
    month = aug,
    year = "2021",
    address = "Online",
    publisher = "Association for Computational Linguistics",
    url = "https://aclanthology.org/2021.acl-long.507",
    doi = "10.18653/v1/2021.acl-long.507",
    pages = "6490--6500",
    abstract = "We show that margin-based bitext mining in a multilingual sentence space can be successfully scaled to operate on monolingual corpora of billions of sentences. We use 32 snapshots of a curated common crawl corpus (Wenzel et al, 2019) totaling 71 billion unique sentences. Using one unified approach for 90 languages, we were able to mine 10.8 billion parallel sentences, out of which only 2.9 billions are aligned with English. We illustrate the capability of our scalable mining system to create high quality training sets from one language to any other by training hundreds of different machine translation models and evaluating them

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dataset_licence({ "id": "SEACrowd/ccmatrix" })
signal: "unclear"
stated_licence: "bsd"
sources: 0