Linguistic Input Features Improve Neural Machine Translation
輸入語言特徵改進神經機器翻譯1 目錄 輸入語言特徵改進神經機器翻譯1 目錄 摘要 介紹 神經網絡機器翻譯 增加輸入特徵 語言學特徵 詞性還原 子標籤 詞法特徵 POS標籤和依賴標籤 關於在子字模型中使用字符級功能 摘要 神經機器翻譯最近取得了令人矚目的成果，同時對外部語言信息的很少使用。在本文中，我們表明神經MT模型的強大學習能力不會使語言特徵冗餘; 它們可以很容易地結合起來，以進一步提高性能。
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相關文章
- 1. 【CS224n】Neural Machine Translation with Seq2Seq
- 2. Paper：Effective Approaches to Attention-based Neural Machine Translation
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- 4. Neural Machine Translation by Jointly Learning to Align and....
- 5. Fine-Grained Attention Mechanism for Neural Machine Translation
- 6. Neural Machine Translation by Jointly Learning to Align and Translate
- 7. Unsupervised Bilingual Word Embedding Agreement for Unsupervised Neural Machine Translation
- 8. NEURAL MACHINE TRANSLATION BY JOINTLY LEARNING TO ALIGN AND TRANSLATE
- 9. 多標籤分類：Google‘s Neural Machine Translation System
- 10. Extract and Edit: An Alternative to Back-Translation for Unsupervised Neural Machine Translation