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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 1601–1650 of 1773 papers

TitleStatusHype
Improving Japanese-to-English Neural Machine Translation by Paraphrasing the Target Language—0
Improving Neural Machine Translation through Phrase-based Forced Decoding—0
Tokyo Metropolitan University Neural Machine Translation System for WAT 2017—0
Patent NMT integrated with Large Vocabulary Phrase Translation by SMT at WAT 2017—0
Understanding and Improving Morphological Learning in the Neural Machine Translation Decoder—0
Key-value Attention Mechanism for Neural Machine Translation—0
CUNI NMT System for WAT 2017 Translation Tasks—0
CKY-based Convolutional Attention for Neural Machine Translation—0
Context-Aware Smoothing for Neural Machine Translation—0
Concept Equalization to Guide Correct Training of Neural Machine Translation—0
Unsupervised Neural Machine TranslationCode0
Paying Attention to Multi-Word Expressions in Neural Machine TranslationCode0
The IIT Bombay English-Hindi Parallel Corpus—0
Enhanced Neural Machine Translation by Learning from DraftCode0
Dynamic Oracle for Neural Machine Translation in Decoding Phase—0
Toward a full-scale neural machine translation in production: the Booking.com use case—0
OpenNMT: Open-source Toolkit for Neural Machine Translation—0
Refining Source Representations with Relation Networks for Neural Machine Translation—0
Information-Propogation-Enhanced Neural Machine Translation by Relation Model—0
University of Rochester WMT 2017 NMT System Submission—0
Incorporating Global Visual Features into Attention-based Neural Machine Translation.—0
Sentence-Level Multilingual Multi-modal Embedding for Natural Language Processing—0
A New Methodology to Maximize the Strength of SMT and NMT—0
Comparative Evaluation of NMT with Established SMT Programs—0
Using Target-side Monolingual Data for Neural Machine Translation through Multi-task Learning—0
Neural Machine Translation with Source Dependency Representation—0
Instance Weighting for Neural Machine Translation Domain AdaptationCode0
Interactive Visualization and Manipulation of Attention-based Neural Machine Translation—0
Feature-rich NMT and SMT post-edited corpora for productivity and evaluation tasks with a subset of MQM-annotated data—0
Towards Decoding as Continuous Optimisation in Neural Machine Translation—0
Towards Compact and Fast Neural Machine Translation Using a Combined Method—0
A Comparative Quality Evaluation of PBSMT and NMT using Professional Translators—0
Automatically Generating Commit Messages from Diffs using Neural Machine Translation—0
Look-ahead Attention for Generation in Neural Machine Translation—0
Handling Homographs in Neural Machine Translation—0
The Helsinki Neural Machine Translation SystemCode0
Neural machine translation for low-resource languages—0
Neural Machine Translation Leveraging Phrase-based Models in a Hybrid Search—0
Memory-augmented Neural Machine Translation—0
Translating Phrases in Neural Machine Translation—0
Neural Machine Translation with Word Predictions—0
Exploiting Linguistic Resources for Neural Machine Translation Using Multi-task Learning—0
Analyzing Neural MT Search and Model Performance—0
Dynamic Data Selection for Neural Machine TranslationCode0
Detecting Untranslated Content for Neural Machine Translation—0
Linguistically Motivated Vocabulary Reduction for Neural Machine Translation from Turkish to English—0
Regularization techniques for fine-tuning in neural machine translation—0
Learning Language Representations for Typology PredictionCode0
Curriculum Learning and Minibatch Bucketing in Neural Machine Translation—0
Machine Translation at Booking.com: Journey and Lessons Learned—0
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