Papers with Mongolian morphological noise

1 papers
Improving Mongolian-Chinese Neural Machine Translation with Morphological Noise (P19-2)

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Challenge: Existing models for Mongolian-Chinese translation are based on recurrent, convolutional neural networks or completely eliminate recurrence connections.
Approach: They propose a adversarial training model to alleviate the UNK problem in Mongolian-Chinese machine translation by adding a screener to the model to emphasize the added Mongolian morphological noise.
Outcome: The proposed model reduces training time and improves accuracy in Mongolian-Chinese translation tasks.

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