A majority of language technologies are tailored for a small number of high-resource languages, while relatively many low-resource languages are neglected. One such group, Creole languages, have long been marginalized in academic study, though their speakers could benefit from machine translation (MT). These languages are predominantly used in much of Latin America, Africa and the Caribbean. We present the largest cumulative dataset to date for Creole language MT, including 14.5M unique Creole sentences with parallel translations -- 11.6M of which we release publicly, and the largest bitexts gathered to date for 41 languages -- the first ever for 21. In addition, we provide MT models supporting all 41 Creole languages in 172 translation directions. Given our diverse dataset, we produce a model for Creole language MT exposed to more genre diversity than ever before, which outperforms a genre-specific Creole MT model on its own benchmark for 26 of 34 translation directions.

翻译：大多数语言技术仅针对少数资源丰富的语言进行定制，而相对较多的低资源语言则被忽视。克里奥尔语群便是其中之一，它们在学术研究中长期处于边缘地位，但其使用者本可以从机器翻译中获益。这些语言主要广泛使用于拉丁美洲、非洲及加勒比地区。我们提出了迄今为止规模最大的克里奥尔语机器翻译累积数据集，包含1450万个独特的克里奥尔语句子及其平行译文——其中1160万句已公开发布，并涵盖迄今收集的41种语言中规模最大的双语平行语料，其中21种语言为首次收录。此外，我们提供了支持全部41种克里奥尔语在172个翻译方向上的机器翻译模型。基于这一多样化数据集，我们训练出的克里奥尔语机器翻译模型所接触的文类多样性超过以往任何同类模型，该模型在34个翻译方向中有26个方向的表现超越了其自有基准测试中面向特定文类的克里奥尔语翻译模型。