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Neural Machine Translation Advised by Statistical Machine Translation
Proceedings of the AAAI Conference on Artificial Intelligence, 2017 Neural Machine Translation (NMT) is a new approach to machine translation that has made great progress in recent years. However, recent studies show that NMT generally produces fluent but inadequate translations (Tu et al. 2016b; 2016a; He et al. 2016; Tu et al. 2017). This is in contrast to conventional Statistical Machine Translation (
Wang, Xing +5 more
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Learning to Translate in Real-time with Neural Machine Translation [PDF]
, 2017 Translating in real-time, a.k.a. simultaneous translation, outputs translation words before the input sentence ends, which is a challenging problem for conventional machine translation methods.
Cho, Kyunghyun +3 more
core +2 more sources
OpenNMT: Open-Source Toolkit for Neural Machine Translation [PDF]
Annual Meeting of the Association for Computational Linguistics, 2017 We describe an open-source toolkit for neural machine translation (NMT). The toolkit prioritizes efficiency, modularity, and extensibility with the goal of supporting NMT research into model architectures, feature representations, and source modalities ...
Guillaume Klein +4 more
semanticscholar +1 more source
Is machine translation a dim technology for its users? An eye tracking study
Frontiers in Psychology, 2023 State-of-the-art research shows that the impact of language technologies on public awareness and attitudes toward using machine translation has been changing.
Ramunė Kasperė +4 more
doaj +1 more source
On Statistical Machine Translation and Translation Theory [PDF]
Proceedings of the Second Workshop on Discourse in Machine Translation, 2015 The translation process in statistical machine translation (SMT) is shaped by technical constraints and engineering considerations. SMT explicitly models translation as search for a target-language equivalent of the input text. This perspective on translation had wide currency in mid-20th century translation studies, but has since been superseded by ...
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Cogent Arts & Humanities, 2023 This study aims to examine machine translation research in journals indexed in the Web of Science to find out the research trending issue, hotspot areas of research, and document co-citation analysis. To this end, 541 documents published between 1992 and
Mohammed Ali Mohsen +2 more
doaj +1 more source
Moses: Open Source Toolkit for Statistical Machine Translation
Annual Meeting of the Association for Computational Linguistics, 2007 We describe an open-source toolkit for statistical machine translation whose novel contributions are (a) support for linguistically motivated factors, (b) confusion network decoding, and (c) efficient data formats for translation models and language ...
Philipp Koehn +13 more
semanticscholar +1 more source
Big Data and Cognitive Computing, 2023 French is a strategically and economically important language in the regions where the African language Twi is spoken. However, only a very small proportion of Twi speakers in Ghana speak French. The development of a Twi–French parallel corpus and corresponding machine translation applications would provide various advantages, including stimulating ...
Frederick Gyasi, Tim Schlippe
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The Machine Translation Leaderboard [PDF]
The Prague Bulletin of Mathematical Linguistics, 2014 Abstract Much of an instructor's time is spent on the management and grading of homework. We present the Machine Translation Leaderboard, a platform for managing, displaying, and automatically grading homework assignments. It runs on Google App Engine, which provides hosting and user management services.
Lopez, Adam, Post, Matt
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Indian Journal of Social Psychiatry, 2019 Background: Questionnaires are forward-translated and then back-translated by human translators during adaptation of a survey questionnaire in the local language. The machine translation method is now available free from “Google Translate” website and it
Himel Mondal +2 more
doaj +1 more source