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NMT

Neural machine translation is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.

Papers

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Showing 1181–1190 of 1773 papers

TitleStatusHype
Differences between SMT and NMT Output - a Translators' Point of View—0
Dependency-Based Self-Attention for Transformer NMT—0
Dependency-Based Relative Positional Encoding for Transformer NMT—0
Human Evaluation of Neural Machine Translation: The Case of Deep Learning—0
Investigating Terminology Translation in Statistical and Neural Machine Translation: A Case Study on English-to-Hindi and Hindi-to-English—0
Bilingual Low-Resource Neural Machine Translation with Round-Tripping: The Case of Persian-Spanish—0
Comparing MT Approaches for Text Normalization—0
Comparing a Hand-crafted to an Automatically Generated Feature Set for Deep Learning: Pairwise Translation Evaluation—0
Combining PBSMT and NMT Back-translated Data for Efficient NMT—0
Exploring Adequacy Errors in Neural Machine Translation with the Help of Cross-Language Aligned Word Embeddings—0
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