Web: http://arxiv.org/abs/2205.15544

Sept. 16, 2022, 1:16 a.m. | Xuan-Phi Nguyen, Shafiq Joty, Wu Kui, Ai Ti Aw

cs.CL updates on arXiv.org arxiv.org

Numerous recent work on unsupervised machine translation (UMT) implies that
competent unsupervised translations of low-resource and unrelated languages,
such as Nepali or Sinhala, are only possible if the model is trained in a
massive multilingual environment, where theses low-resource languages are mixed
with high-resource counterparts. Nonetheless, while the high-resource languages
greatly help kick-start the target low-resource translation tasks, the language
discrepancy between them may hinder their further improvement. In this work, we
propose a simple refinement procedure to disentangle languages …

arxiv language translation unsupervised

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