Web: http://arxiv.org/abs/2209.10875

Sept. 23, 2022, 1:15 a.m. | Qiao Cheng, Jin Huang, Yitao Duan

cs.CL updates on arXiv.org arxiv.org

This paper introduces a new data augmentation method for neural machine
translation that can enforce stronger semantic consistency both within and
across languages. Our method is based on Conditional Masked Language Model
(CMLM) which is bi-directional and can be conditional on both left and right
context, as well as the label. We demonstrate that CMLM is a good technique for
generating context-dependent word distributions. In particular, we show that
CMLM is capable of enforcing semantic consistency by conditioning on both …

arxiv augmentation consistent data language language model machine machine translation neural machine translation translation

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