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Mar 23, 2024 · Neural networks for machine translation typically contain an encoder reading the input sentence and generating a representation of it. A decoder then generates the output sentence word by word while consulting the representation generated by the encoder. The Transformer starts by generating initial representations, or embeddings, for each word...
The central idea of deep learning is that optimizing a number of subsequent nonlinear processing layers on a global objective, such as translation quality, enables these layers to automatically form intermediate representations, typically on different levels of abstraction, that are helpful in solving the task at hand.
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5 days ago · Abstract. Transformer is the state-of-the-art model in recent machine translation evaluations. Two strands of research are promising to improve models of this kind: the first uses wide networks (a.k.a. Transformer-Big) and has been the de facto standard for development of the Transformer system, and the other uses deeper language representation ...
- Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F. Wong, Lidia S. Chao
- 2019
Jun 5, 2019 · Abstract: Transformer is the state-of-the-art model in recent machine translation evaluations. Two strands of research are promising to improve models of this kind: the first uses wide networks (a.k.a. Transformer-Big) and has been the de facto standard for the development of the Transformer system, and the other uses deeper language ...
- Qiang Wang, Bei Li, Tong Xiao, Jingbo Zhu, Changliang Li, Derek F. Wong, Lidia S. Chao
- 2019
Oct 11, 2019 · Multilingual machine translation processes multiple languages using a single translation model. The success of multilingual training for data-scarce languages has been demonstrated for automatic speech recognition and text-to-speech systems, and by prior research on multilingual translation [ 1, 2, 3 ].
May 24, 2018 · Machine translation (MT) is an important natural language processing task that investigates the use of computers to translate human languages automatically. Deep learning-based methods have made significant progress in recent years and quickly become the new de facto paradigm of MT in both academia and industry.
a deep representation by a six-layer encoder, which is subsequently decoded by a six-layer decoder into the translation in the target language. Layers of the encoder and decoder consist of self ...
