Papers with quality translation model

1 papers
Neural Machine Translation for Bilingually Scarce Scenarios: a Deep Multi-Task Learning Approach (N18-1)

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Challenge: Neural machine translation requires large amount of parallel training text to learn a reasonable quality translation model.
Approach: They propose a multi-task learning approach that leverages monolingual linguistic resources in the source side of a machine translation task.
Outcome: The proposed approach is effective on three translation tasks: English-to-French, English- to-Farsi, and English-à-Vietnamese.

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