Add to ORKGThis research was reported in the trade magazine Slator: Language Industry Intelligence in Oct 2016 as “Significant progress in real-time machine translation."Session 7A: Machine Translation and Multilingualitypostprin
In interactive machine translation (MT), human translators correct errors in automatic translations ...
Neural machine translation (NMT) has emerged recently as a promising alternative of standard rule-ba...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Simultaneous neural Machine Translation (SiMT) aims to maintain translation quality while minimizing...
Humans benefit from communication but suffer from language barriers. Machine translation (MT) aims t...
We present a Deep Reinforcement Learning based approach for the task of real time machine translatio...
With economic globalization and the rapid development of the Internet, the connections between diffe...
We introduce a reinforcement learning-based approach to simultaneous ma-chine translation—producing ...
Neural Machine Translation is the primary algorithm used in industry to perform machine translation....
Simultaneous machine translation systems rely on a policy to schedule read and write operations in o...
Neural machine translation (NMT), where neural networks are used to generate translations, has revol...
Hybrid machine translation (HMT) takes advantage of different types of machine translation (MT) sys...
The last few years have witnessed a surge in the interest of a new machine translation paradigm: neu...
Simultaneous machine translation (SIMT) involves translating source utterances to the target languag...
In recent years, neural machine translation (NMT) has demonstrated state-of-the-art machine transla...
In interactive machine translation (MT), human translators correct errors in automatic translations ...
Neural machine translation (NMT) has emerged recently as a promising alternative of standard rule-ba...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...
Simultaneous neural Machine Translation (SiMT) aims to maintain translation quality while minimizing...
Humans benefit from communication but suffer from language barriers. Machine translation (MT) aims t...
We present a Deep Reinforcement Learning based approach for the task of real time machine translatio...
With economic globalization and the rapid development of the Internet, the connections between diffe...
We introduce a reinforcement learning-based approach to simultaneous ma-chine translation—producing ...
Neural Machine Translation is the primary algorithm used in industry to perform machine translation....
Simultaneous machine translation systems rely on a policy to schedule read and write operations in o...
Neural machine translation (NMT), where neural networks are used to generate translations, has revol...
Hybrid machine translation (HMT) takes advantage of different types of machine translation (MT) sys...
The last few years have witnessed a surge in the interest of a new machine translation paradigm: neu...
Simultaneous machine translation (SIMT) involves translating source utterances to the target languag...
In recent years, neural machine translation (NMT) has demonstrated state-of-the-art machine transla...
In interactive machine translation (MT), human translators correct errors in automatic translations ...
Neural machine translation (NMT) has emerged recently as a promising alternative of standard rule-ba...
Neural machine translation (NMT) conducts end-to-end translation with a source language encoder and ...