Papers with multi-lingual system

1 papers
Universal Neural Machine Translation for Extremely Low Resource Languages (N18-1)

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Challenge: a novel multilingual approach to machine translation is proposed for low resource languages . the proposed approach can achieve 23 BLEU on Romanian-English WMT2016 using a tiny parallel corpus of 6k sentences compared to the 18 BLUE of strong baseline system .
Approach: They propose a transfer-learning approach to share lexical and sentence representations across multiple source languages into one target language.
Outcome: The proposed approach achieves 23 BLEU on Romanian-English WMT2016 using a tiny parallel corpus of 6k sentences compared to the 18 BLUE of strong baseline system which uses multi-lingual training and back-translation.

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