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- Neural machine translation, or NMT for short, is the use of neural network models to learn a statistical model for machine translation. The key benefit to the approach is that a single system can be trained directly on source and target text, no longer requiring the pipeline of specialized systems used in statistical machine learning.
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Neural machine translation (NMT) is an approach to machine translation that uses an artificial neural network to predict the likelihood of a sequence of words, typically modeling entire sentences in a single integrated model.
Jan 1, 2020 · Understanding how and why NMT produces its translation result is important to figure out the bottleneck and weakness of NMT models. Designing better architectures. Designing a new architecture that better than Transformer is beneficial for both NMT research and production.
- Zhixing Tan, Shuo Wang, Zonghan Yang, Gang Chen, Xuancheng Huang, Maosong Sun, Yang Liu
- 2020
Jun 3, 2019 · Machine Translation (MT) is a subfield of computational linguistics that is focused on translating text from one language to another. With the power of deep learning, Neural Machine Translation (NMT) has arisen as the most powerful algorithm to perform this task.
Dec 18, 2017 · 3 Reasons Why Neural Machine Translation is a Breakthrough. Neural machine translation (NMT) reduces post-editing effort by 25%, outputs more fluent translations, and “linguistically speaking it also seems in quite a few categories that it actually outperforms statistical machine translation (SMT).”. This comparison opened Samuel Läubli ...
In recent years, end-to-end neural machine translation (NMT) has achieved great success and has become the new mainstream method in practical MT systems. In this article, we first provide a broad review of the methods for NMT and focus on methods relating to architectures, decoding, and data augmentation.
- Zhixing Tan, Shuo Wang, Zonghan Yang, Gang Chen, Xuancheng Huang, Maosong Sun, Yang Liu
- 2020
Oct 30, 2021 · In recent years, neural network-based machine translation (MT) approaches have steadily superseded the statistical MT (SMT) methods, and represents the current state-of-the-art in MT research. Neural MT (NMT) is a data-driven end-to-end learning protocol whose training routine usually requires a large amount of parallel data in order to build a ...
1 NMT and legal translation: introductory remarks There are many myths about neural machine translation (NMT) (see do Carmo 2022) as well as deep concerns about the role (specialised) translators play in the age of automation.1 The scary idea of ‘human parity’, i. e. the belief that NMT can achieve the
