通过多语言转移学习利用跨领域平行数据进行低资源神经机器翻译的开发

Jul, 2019

Exploiting Out-of-Domain Parallel Data through Multilingual Transfer Learning for Low-Resource Neural Machine Translation

Aizhan Imankulova, Raj Dabre, Atsushi Fujita, Kenji Imamura

TL;DR本文提出了一种新的多语种多阶段微调方法，融合了领域自适应、多语言和反向翻译，通过利用域外数据的转移学习方法来帮助改善日俄低资源神经机器翻译的质量。

Abstract

This paper proposes a novel multilingual multistage fine-tuning approach for low-resource neural machine translation (NMT), taking a chall