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Linguistic Input Features Improve Neural Machine Translation
時間 2021-01-07
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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
3.
[EMNLP2015]Effective Approaches to Attention-based Neural Machine Translation
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
>>更多相關文章<<