Incorporating bilingual translation templates into neural machine translation

Incorporating bilingual translation templates into neural machine translation

Blog Article

Abstract In the neural machine translation (NMT) paradigm, transformer-based NMT has achieved great progress in recent years.It uses parallel corpus and is based on the stand end-to-end structure.Inspired by the process of translating sentences by translators and the Lift Arm Wheel success of templates in other natural language processing tasks, a new method is proposed to incorporate the bilingual translation templates into the Transformer-based NMT.

Firstly, the template extraction method is proposed to generate the parallel templates corpus base on the constituency parse tree.Next, given a sentence to be translated, a fuzzy matching method is proposed to calculate the most Equine - Grooming - Sweat Scrapers possible target translation template from the parallel template corpus.Finally, an effective method is proposed to incorporate the bilingual templates into the Transformer-based NMT decoder.

Experiment results achieved in three translation tasks show the effectiveness of the proposed approach.