Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder

时间 2020-12-30

标签 NLP 自然语言处理机器翻译无监督机器翻译无监督神经机器翻译栏目 Microsoft Office 繁體版

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Improving Unsupervised Word-by-Word Translation with Language Model and Denoising Autoencoder 知识点摘要引言 Cross-lingual Word Embedding Sentence Translation 3.1 Context-aware Beam Search 3.2 Denoising 实验

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1. Revisiting Adversarial Autoencoder for Unsupervised Word Translation with Cycle Consistency and...
2. Denoising Autoencoder
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5. Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention 解读
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1. Revisiting Adversarial Autoencoder for Unsupervised Word Translation with Cycle Consistency and...
2. Denoising Autoencoder
3. IMPROVING GENERATIVE ADVERSARIAL NETWORKS WITH DENOISING FEATURE MATCHING（Bingio-ICLR2017）
4. language model and RNN
5. Show, Attend and Translate: Unsupervised Image Translation with Self-Regularization and Attention 解读
6. Translation with a Sequence to Sequence Network and Attention
7. Multimodal——Paper笔记：Improving Vision-and-Language Navigation with Image-Text Pairs from the Web
8. Language Modeling with N-grams (Speech and Language Processing)
9. Multilingual Unsupervised NMT using Shared Encoder and Language-Specific Decoders
10. Extract and Edit: An Alternative to Back-Translation for Unsupervised Neural Machine Translation

>>更多相关文章<<