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Incorporating bilingual translation templates into neural machine translation [PDF]
Scientific ReportsIn the neural machine translation (NMT) paradigm, transformer-based NMT has achieved great progress in recent years. It uses parallel corpus and is based on the stand end-to-end structure.
Fuxue Li +5 more
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Neural Machine Translation [PDF]
Revista Tradumàtica, 2017 From the outset, automatic translation was dominated by systems based on linguistic information, but then later other approaches opened up the way, such as translation memories and statistical machine translation which draw on parallel language corpora ...
Francisco Casacuberta Nolla +1 more
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Sublemma-Based Neural Machine Translation [PDF]
Complexity, 2021 Powerful deep learning approach frees us from feature engineering in many artificial intelligence tasks. The approach is able to extract efficient representations from the input data, if the data are large enough. Unfortunately, it is not always possible
Thien Nguyen, Huu Nguyen, Phuoc Tran
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The neural machine translation models for the low-resource Kazakh–English language pair [PDF]
PeerJ Computer Science, 2023 The development of the machine translation field was driven by people’s need to communicate with each other globally by automatically translating words, sentences, and texts from one language into another.
Vladislav Karyukin +4 more
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Mixed-Level Neural Machine Translation. [PDF]
Comput Intell Neurosci, 2020 Building the first Russian-Vietnamese neural machine translation system, we faced the problem of choosing a translation unit system on which source and target embeddings are based. Available homogeneous translation unit systems with the same translation unit on the source and target sides do not perfectly suit the investigated language pair.
Nguyen T, Nguyen H, Tran P.
europepmc +4 more sources
Translating Akkadian to English with neural machine translation. [PDF]
PNAS Nexus, 2023 Abstract Cuneiform is one of the earliest writing systems in recorded human history (ca. 3,400 BCE–75 CE). Hundreds of thousands of such texts were found over the last two centuries, most of which are written in Sumerian and Akkadian.
Gutherz G +4 more
europepmc +3 more sources
Generative Neural Machine Translation [PDF]
, 2018 We introduce Generative Neural Machine Translation (GNMT), a latent variable architecture which is designed to model the semantics of the source and target sentences.
Barber, David, Shah, Harshil
core +3 more sources
Semantic Neural Machine Translation Using AMR [PDF]
Transactions of the Association for Computational Linguistics, 2019 It is intuitive that semantic representations can be useful for machine translation, mainly because they can help in enforcing meaning preservation and handling data sparsity (many sentences correspond to one meaning) of machine translation models.
Song, Linfeng +4 more
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Survey of Mongolian-Chinese Neural Machine Translation [PDF]
Jisuanji kexue, 2022 Machine translation is the process of using a computer to convert one language into another language.With the deep understanding of semantics,neural machine translation has become the most mainstream machine translation method at present,and it has made ...
HOU Hong-xu, SUN Shuo, WU Nier
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Machine Translation Systems for English Captions to Hindi Language Using Deep Learning [PDF]
ITM Web of Conferences, 2022 Machine Translation is the process of translating text from one language to another which helps to reduce the conversation gap among people from different cultural backgrounds.
Singh Arvinder +3 more
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