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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 271–280 of 1773 papers

TitleStatusHype
Benefits of Data Augmentation for NMT-based Text Normalization of User-Generated Content—0
Benchmarking Neural and Statistical Machine Translation on Low-Resource African Languages—0
An Empirical Analysis of NMT-Derived Interlingual Embeddings and their Use in Parallel Sentence Identification—0
ConECT Dataset: Overcoming Data Scarcity in Context-Aware E-Commerce MT—0
Constraint Translation Candidates: A Bridge between Neural Query Translation and Cross-lingual Information Retrieval—0
Content-Equivalent Translated Parallel News Corpus and Extension of Domain Adaptation for NMT—0
Benchmarking Azerbaijani Neural Machine Translation—0
An Effective Optimization Method for Neural Machine Translation: The Case of English-Persian Bilingually Low-Resource Scenario—0
Being Generous with Sub-Words towards Small NMT Children—0
Beam Search Strategies for Neural Machine Translation—0
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