Titlebook: Joint Training for Neural Machine Translation; Yong Cheng Book 2019 Springer Nature Singapore Pte Ltd. 2019 Machine Translation.Neural Mac

小天使

書目名稱Joint Training for Neural Machine Translation影響因子(影響力)




書目名稱Joint Training for Neural Machine Translation影響因子(影響力)學(xué)科排名




書目名稱Joint Training for Neural Machine Translation網(wǎng)絡(luò)公開度




書目名稱Joint Training for Neural Machine Translation網(wǎng)絡(luò)公開度學(xué)科排名




書目名稱Joint Training for Neural Machine Translation被引頻次




書目名稱Joint Training for Neural Machine Translation被引頻次學(xué)科排名




書目名稱Joint Training for Neural Machine Translation年度引用




書目名稱Joint Training for Neural Machine Translation年度引用學(xué)科排名




書目名稱Joint Training for Neural Machine Translation讀者反饋




書目名稱Joint Training for Neural Machine Translation讀者反饋學(xué)科排名

量被毀壞

Agreement-Based Joint Training for Bidirectional Attention-Based Neural Machine Translation,n the same training data. Experiments on ChineseEnglish and English-French translation tasks show that agreement-based joint training significantly improves both alignment and translation quality over independent training.

Distribution

Semi-supervised Learning for Neural Machine Translation,et and target-to-source translation models serve as the encoder and decoder, respectively. Our approach can not only exploit the monolingual corpora of the target language, but also of the source language. Experiments on the ChineseEnglish dataset show that our approach achieves significant improvements over state-of-the-art SMT and NMT systems.

AMITY

Herd-Immunity

越自我

MOTTO

subordinate

Book 2019 of the attention mechanism, it proposes an agreement-based joint training approach to help the two complementary models agree on word alignment matrices for the same training data. Second, it presents a semi-supervised approach that uses an autoencoder to reconstruct monolingual corpora, so as to i

HATCH

發(fā)起

Related Work,T. Next we summarize a number of work which incorporate additional data resources, such as monolingual corpora and pivot language corpora, into machine translation systems. Finally, we make a simple review of the studies about contrastive learning, which is a key technique in our fourth work.