A Survey on Low-Resource Neural Machine Translation

Wang, Rui; Tan, Xu; Luo, Renqian; Qin, Tao; Liu, Tie-Yan

doi:10.24963/ijcai.2021/629

A Survey on Low-Resource Neural Machine Translation

Rui Wang, Xu Tan, Renqian Luo, Tao Qin, Tie-Yan Liu

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Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence. Survey Track. Pages 4636-4643.

https://doi.org/10.24963/ijcai.2021/629

Keywords

Natural language processing: General
Machine learning: General

Abstract

Neural approaches have achieved state-of-the-art accuracy on machine translation but suffer from the high cost of collecting large scale parallel data. Thus, a lot of research has been conducted for neural machine translation (NMT) with very limited parallel data, i.e., the low-resource setting. In this paper, we provide a survey for low-resource NMT and classify related works into three categories according to the auxiliary data they used: (1) exploiting monolingual data of source and/or target languages, (2) exploiting data from auxiliary languages, and (3) exploiting multi-modal data. We hope that our survey can help researchers to better understand this field and inspire them to design better algorithms, and help industry practitioners to choose appropriate algorithms for their applications.

Rui Wang, Xu Tan, Renqian Luo, Tao Qin, and Tie-Yan Liu. 2021. A Survey on Low-Resource Neural Machine Translation. In Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21. IJCAI, 4636–4643. https://doi.org/10.24963/ijcai.2021/629

@inproceedings{ijcai2021p629,
  title     = {A Survey on Low-Resource Neural Machine Translation},
  author    = {Wang, Rui and Tan, Xu and Luo, Renqian and Qin, Tao and Liu, Tie-Yan},
  booktitle = {Proceedings of the Thirtieth International Joint Conference on
               Artificial Intelligence, {IJCAI-21}},
  publisher = {International Joint Conferences on Artificial Intelligence Organization},
  editor    = {Prof. Zhi-Hua Zhou},
  pages     = {4636--4643},
  year      = {2021},
  month     = {8},
  note      = {Survey Track},
  doi       = {10.24963/ijcai.2021/629},
  url       = {https://doi.org/10.24963/ijcai.2021/629},
}

TY  - CPAPER
TI  - A Survey on Low-Resource Neural Machine Translation
AU  - Wang, Rui
AU  - Tan, Xu
AU  - Luo, Renqian
AU  - Qin, Tao
AU  - Liu, Tie-Yan
T2  - Proceedings of the Thirtieth International Joint Conference on Artificial Intelligence, IJCAI-21
PB  - International Joint Conferences on Artificial Intelligence Organization
PY  - 2021
SP  - 4636
EP  - 4643
DO  - 10.24963/ijcai.2021/629
UR  - https://doi.org/10.24963/ijcai.2021/629
ER  -