Results 61 to 70 of about 238,882 (174)
Unsupervised Multi-Modal Neural Machine Translation [PDF]
2019 IEEE/CVF Conference on Computer Vision and Pattern Recognition (CVPR), 2019 Accepted to CVPR ...
Su, Yuanhang +4 more
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Discover ComputingThe decoding phase is a crucial component in machine translation systems, alongside the creation of the model. Beam search is the most commonly used algorithm for decoding in these systems.
Emre Satir, Hasan Bulut
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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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A Challenge Set Approach to Evaluating Machine Translation
, 2017 Neural machine translation represents an exciting leap forward in translation quality. But what longstanding weaknesses does it resolve, and which remain?
Cherry, Colin +2 more
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A review of existing Machine Translation Approaches, their Challenges and Evaluation Metrics
Pakistan Journal of Engineering Technology & Science, 2023 Machine translation is the process of translating a natural language into another. The primary goal of machine translation is to bridge the linguistic gap between languages.
Naseer Ahmed
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Handling Homographs in Neural Machine Translation
, 2018 Homographs, words with different meanings but the same surface form, have long caused difficulty for machine translation systems, as it is difficult to select the correct translation based on the context.
Liu, Frederick, Lu, Han, Neubig, Graham
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Neural machine translation system for the Kazakh language based on synthetic corpora
MATEC Web of Conferences, 2019 The lack of big parallel data is present for the Kazakh language. This problem seriously impairs the quality of machine translation from and into Kazakh.
Tukeyev Ualsher +2 more
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Custom neural machine translation
, 2022 This chapter gives an overview of the theoretical and practical implications of customizing machine translation (MT) to make it fit for a particular purpose. The chapter is written for readers who have just a basic knowledge of MT, but experts who are seeking new ways of explaining MT to non-experts may also find it useful.
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Synchronous Bidirectional Neural Machine Translation
Transactions of the Association for Computational Linguistics, 2019 Existing approaches to neural machine translation (NMT) generate the target language sequence token-by-token from left to right. However, this kind of unidirectional decoding framework cannot make full use of the target-side future contexts which can be ...
Zhou, Long +2 more
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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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