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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 1301–1310 of 1773 papers

TitleStatusHype
Semantic Diversity by Phonetics for Accurate and Robust Machine Translation—0
Revisiting Low-Resource Neural Machine Translation: A Case StudyCode0
Debiasing Word Embeddings Improves Multimodal Machine Translation—0
An Analysis of Source-Side Grammatical Errors in NMT—0
Corpus Augmentation by Sentence Segmentation for Low-Resource Neural Machine Translation—0
Target Conditioned Sampling: Optimizing Data Selection for Multilingual Neural Machine Translation—0
When a Good Translation is Wrong in Context: Context-Aware Machine Translation Improves on Deixis, Ellipsis, and Lexical CohesionCode1
Effective Cross-lingual Transfer of Neural Machine Translation Models without Shared VocabulariesCode0
Synchronous Bidirectional Neural Machine TranslationCode0
Syntax-Enhanced Neural Machine Translation with Syntax-Aware Word Representations—0
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