ProLanGO: Protein Function Prediction Using Neural Machine Translation Based on a Recurrent Neural Network. [PDF]
Molecules, 2017 Cao R +5 more
europepmc +3 more sources
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
doaj +1 more source
CURE: Code-Aware Neural Machine Translation for Automatic Program Repair [PDF]
International Conference on Software Engineering, 2021 Automatic program repair (APR) is crucial to improve software reliability. Recently, neural machine translation (NMT) techniques have been used to automatically fix software bugs. While promising, these approaches have two major limitations. Their search
Nan Jiang, Thibaud Lutellier, Lin Tan
semanticscholar +1 more source
Exploring the evolution and future prospects of Amharic to English machine translation: a systematic review [PDF]
Frontiers in Artificial IntelligenceIntroductionIn the last couple of decades, Amharic-English translation has greatly improved from a rule-based approach to contemporary systems that apply neural networks.
Muluken Hussen Asebel +2 more
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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
doaj +1 more source
Revisiting Negation in Neural Machine Translation [PDF]
Transactions of the Association for Computational Linguistics, 2021 In this paper, we evaluate the translation of negation both automatically and manually, in English–German (EN–DE) and English– Chinese (EN–ZH). We show that the ability of neural machine translation (NMT) models to translate negation has improved with deeper and more advanced networks, although the performance varies between language pairs and ...
Gongbo Tang +4 more
openaire +5 more sources
Scaling Laws for Multilingual Neural Machine Translation [PDF]
International Conference on Machine Learning, 2023 In this work, we provide a large-scale empirical study of the scaling properties of multilingual neural machine translation models. We examine how increases in the model size affect the model performance and investigate the role of the training mixture ...
Patrick Fernandes +4 more
semanticscholar +1 more source
Multilingual Denoising Pre-training for Neural Machine Translation [PDF]
Transactions of the Association for Computational Linguistics, 2020 This paper demonstrates that multilingual denoising pre-training produces significant performance gains across a wide variety of machine translation (MT) tasks.
Yinhan Liu +7 more
semanticscholar +1 more source
Advance Research on Neural Machine Translation Integrating Linguistic Knowledge
Jisuanji kexue yu tansuo, 2021 Although neural machine translation has become the mainstream method and paradigm in the current research and application of machine translation, there are also some problems such as the fluent but not faithful of the translation results, difficult ...
GUO Wanghao, FAN Jiangwei, ZHANG Keliang
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A Survey on Hybrid Machine Translation [PDF]
E3S Web of Conferences, 2020 Machine translation has gradually developed in past 1940’s.It has gained more and more attention because of effective and efficient nature. As it makes the translation automatically without the involvement of human efforts. The distinct models of machine
Anugu Anusha, Ramesh Gajula
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