Linguistically motivated augmentation beats naive random augmentation in low-resource translation and glossing only when its outputs resemble the natural training data.
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Is linguistically-motivated data augmentation worth it?
Linguistically motivated augmentation beats naive random augmentation in low-resource translation and glossing only when its outputs resemble the natural training data.