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Similarity-aware Neural Machine Translation: Reducing Human Translator Efforts by Leveraging High-potential Sentences with Translation Memory

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Introduction

Similarity-aware-NMT provides a general NMT framework to incorporate multiple dimensional translation memory based features as prior knowledge into Neural Machine Translation. Meanwhile, Similarity-aware-NMT preprocesses the testing set to get high-potential testing set, like string high-potential,structural high-potential and temporal high-potential Please refer to the following paper for details:

Tianfu Zhang, Heyan Huang, Chong Feng, Xiaochi Wei. 2020. Similarity-aware neural machine translation: reducing human translator efforts by leveraging high-potential sentences with translation memory. Neural Computing and Applications, pp. 1–13.2020.

Installation

Similarity-aware-NMT is built on top of THUMT. It requires THEANO 0.8.2 or above version (0.8.2 is recommended)

pip install theano==0.8.2

License

The source code is dual licensed. Open source licensing is under the BSD-3-Clause, which allows free use for research purposes.

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Similarity-aware Neural Machine Translation: Reducing Human Translator Efforts by Leveraging High-potential Sentences with Translation Memory

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