Common Contracts
2 similar null contracts
Agreement on Target-bidirectional Neural Machine TranslationMarch 22nd, 2016
Neural machine translation (NMT) with re- current neural networks, has proven to be an effective technique for end-to-end machine translation. However, in spite of its promis- ing advances over traditional translation meth- ods, it typically suffers from an issue of unbal- anced outputs, that arise from both the nature of recurrent neural networks themselves, and the challenges inherent in machine translation. To overcome this issue, we propose an agree- ment model for neural machine translation and show its effectiveness on large-scale Japanese- to-English and Chinese-to-English translation tasks. Our results show the model can achieve improvements of up to 1.4 BLEU over the strongest baseline NMT system. With the help of an ensemble technique, this new end-to-end NMT approach finally outperformed phrase- based and hierarchical phrase-based Moses baselines by up to 5.6 BLEU points.
Agreement on Target-bidirectional Neural Machine TranslationMarch 22nd, 2016
Neural machine translation (NMT) with re- current neural networks, has proven to be an effective technique for end-to-end machine translation. However, in spite of its promis- ing advances over traditional translation meth- ods, it typically suffers from an issue of unbal- anced outputs, that arise from both the nature of recurrent neural networks themselves, and the challenges inherent in machine translation. To overcome this issue, we propose an agree- ment model for neural machine translation and show its effectiveness on large-scale Japanese- to-English and Chinese-to-English translation tasks. Our results show the model can achieve improvements of up to 1.4 BLEU over the strongest baseline NMT system. With the help of an ensemble technique, this new end-to-end NMT approach finally outperformed phrase- based and hierarchical phrase-based Moses baselines by up to 5.6 BLEU points.
