Results 121 to 130 of about 3,692,894 (287)

Chinese-English machine translation model based on transfer learning and self-attention

Journal of Applied Science and Engineering
With the continuous development of machine learning and neural networks, neural machine translation (NMT) has been widely used due to its strong translation ability.
Shu Ma
doaj   +1 more source

Neural Machine Translation for Indian Languages

Journal of Intelligent Systems, 2019
Machine Translation bridges communication barriers and eases interaction among people having different linguistic backgrounds. Machine Translation mechanisms exploit a range of techniques and linguistic resources for translation prediction.
Pathak Amarnath, Pakray Partha
doaj   +1 more source

Domain robustness in neural machine translation

CoRR, 2019
Translating text that diverges from the training domain is a key challenge for machine translation. Domain robustness---the generalization of models to unseen test domains---is low for both statistical (SMT) and neural machine translation (NMT). In this paper, we study the performance of SMT and NMT models on out-of-domain test sets.
Müller, Mathias, Rios, Annette, Sennrich, Rico   +2 more
openaire   +5 more sources

Neural Machine Translation

International Journal for Research in Applied Science and Engineering Technology, 2022
Abstract: The project's novelty is not merely importing modules and preparing data and feeding the data to the model but understanding how the real language translation works and implementing the logics underlying each method utilized and creating every function from scratch, resulting in the creationof a Neural Machine Translation model.
openaire   +1 more source

Fabrication Routes for Ionic Conducting Fiber Strain Sensors

Advanced Engineering Materials, EarlyView.
Ionic conducting fiber strain sensors (ICFSs) offer compliant, textile‐integrable sensing. Thus far, the commercialization of ICFSs has been constrained by fiber fabrication routes. This review provides a fabrication‐centric analysis of ICFSs correlating processing strategies with material properties and scalability.
Leo John Kershaw, Zhanhong Yang, Anne Ladegaard Skov, Magdalena Skowyra   +3 more
wiley   +1 more source

Supporting AI Readiness Through Digital Workflows in Materials Science

Advanced Engineering Materials, EarlyView.
Digitalization drives innovation in materials science by connecting data silos and turning heterogeneous processes into reusable research pipelines. Across 13 MaterialDigital projects, digital workflows reveal complementary pathways toward AI‐ready materials research, founded on structured data, persistent artifacts, executable orchestration, and ...
Marian Bruns, Lateef Abdul, Stephan Barth, Martin Glauer, Manuel Günther, Fabian Neuhaus, Jan‐Ole Perschewski, Thomas Bjarsch, Henrik Abel, Johannes Bosch, Niklas Meyer, Peter Hofmann, Marc Drechsler, Alexander Dyck, Dhanunjaya Kumar Nerella, Marvin Tegeler, Oleg Shchyglo, Ingo Steinbach, Timo Klecker, Henk Birkholz, Ehsan Borzabadi Farahani, Bernard Fedelich, Cetin Haftaoglu, Tarakeshwar Lakshmipathy, Elena Garcia Trelles, Christoph Schweizer, Reza Darvishi Kamachali, Lukas Koschmieder, Janin Eiken, Markus Apel, Sung‐Min Wi, Jiangdong Zhao, Andreas Fezer, Nicolas Christ, Patrick Schneider, Eldor Urinov, Veit Königer, Volker Knoblauch, Janik Harter, Thomas Seifert, Thitichai Janpheng, Florian Fuchs, Fabian Teichert, Jörg Schuster, Anke Bardehle, Andreas Limper, Ulrich Giese, Carlos Lucke, Mario Beiner, Christoph Gögelein, Lisa Leuchtenberger‐Engel, Christian Hopmann, Felix Wentzien, Heike Wittek, Benjamin Klie, Alexander Röhrs, Ludger Overmeyer, Achraf Atila, Marcel Sadowski, Leopold Talirz, Jan Janssen, Jesper R. Pedersen, Peter Beck, Tejs Vegge, Ivano E. Castelli, Wolfgang Wenzel, Tilmann Hickel, Jörg Schaarschmidt   +67 more
wiley   +1 more source

Improving the post-editing experience using translation recommendation: a user study [PDF]

, 2010
We report findings from a user study with professional post-editors using a translation recommendation framework (He et al., 2010) to integrate Statistical Machine Translation (SMT) output with Translation Memory (TM) systems.
He, Yifan, Way, Andy, Roturier, Johann, van Genabith, Josef, Ma, Yanjun   +4 more
core   +2 more sources

Investigating Backtranslation in Neural Machine Translation

CoRR, 2018
This research has been supported by the ADAPT Centre for Digital Content Technology which is funded under the SFI Research Centres Programme (Grant 13/RC/2106) and is co-funded under the European Regional Development Fund. This work has also received funding from the European Union’s Horizon 2020 research and innovation programme under the Marie ...
Poncelas, Alberto, Shterionov, Dimitar, Way, Andy, Maillette de Buy Wenniger, Gideon, Passban, Peyman   +4 more
openaire   +6 more sources

Emerging Post‐CMOS Hardware Neurons for Brain‐Inspired Computing: Devices, Circuits, and System Integration

Advanced Functional Materials, EarlyView.
The physical realization of artificial neurons is a critical challenge for energy‐efficient neuromorphic computing. This review presents a comprehensive analysis of the evolution of artificial neuron implementations from conventional CMOS to emerging post‐CMOS technologies.
Kannan Udaya Mohanan, Hocheon Yoo, Benoît H. Lessard, Ioannis Kymissis, Chang‐Hyun Kim   +4 more
wiley   +1 more source

Neural Machine Translation System for English to Indian Language Translation Using MTIL Parallel Corpus

Journal of Intelligent Systems, 2019
Introduction of deep neural networks to the machine translation research ameliorated conventional machine translation systems in multiple ways, specifically in terms of translation quality.
Premjith B., Kumar M. Anand, Soman K.P.
doaj   +1 more source