Results 81 to 90 of about 491,933 (328)
DESIGN OF TRANSLATION AMBIGUITY ELIMINATION METHOD BASED ON RECURRENT NEURAL NETWORKS [PDF]
Acta Informatica MalaysiaThe ambiguity of language inevitably leads to the ambiguity of translation, and how to deal with translation ambiguity has become a persistent focus of attention for both human translation and machine translation.
Jianzhou Cui
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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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Machine translation of English speech: Comparison of multiple algorithms
Journal of Intelligent Systems, 2022 In order to improve the efficiency of the English translation, machine translation is gradually and widely used. This study briefly introduces the neural network algorithm for speech recognition.
Wu Yijun, Qin Yonghong
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Measuring and Mitigating Name Biases in Neural Machine Translation
Annual Meeting of the Association for Computational Linguistics, 2022 Neural Machine Translation (NMT) systems exhibit problematic biases, such as stereotypical gender bias in the translation of occupation terms into languages with grammatical gender. In this paper we describe a new source of bias prevalent in NMT systems,
Jun Wang +2 more
semanticscholar +1 more source
Unsupervised Neural Machine Translation
, 2017 In spite of the recent success of neural machine translation (NMT) in standard benchmarks, the lack of large parallel corpora poses a major practical problem for many language pairs. There have been several proposals to alleviate this issue with, for instance, triangulation and semi-supervised learning techniques, but they still require a strong cross ...
Artetxe Zurutuza, Mikel +3 more
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Amharic-arabic Neural Machine Translation [PDF]
5th International Conference on Data Mining and Applications (DMAP 2019), 2019 Many automatic translation works have been addressed between major European language pairs, by taking advantage of large scale parallel corpora, but very few research works are conducted on the Amharic-Arabic language pair due to its parallel data scarcity.
H. L. Shashirekha, Ibrahim Gashaw
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Improving Transformer-Based Neural Machine Translation with Prior Alignments
Complexity, 2021 Transformer is a neural machine translation model which revolutionizes machine translation. Compared with traditional statistical machine translation models and other neural machine translation models, the recently proposed transformer model radically ...
Thien Nguyen +3 more
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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
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Reinforcement Learning for Bandit Neural Machine Translation with Simulated Human Feedback
, 2017 Machine translation is a natural candidate problem for reinforcement learning from human feedback: users provide quick, dirty ratings on candidate translations to guide a system to improve.
Boyd-Graber, Jordan +2 more
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International Journal of Computer Vision, 2020 We present a novel approach to automatic Sign Language Production using recent developments in Neural Machine Translation (NMT), Generative Adversarial Networks, and motion generation.
Stephanie Stoll +3 more
semanticscholar +1 more source