Low resource machine translation of english–manipuri: A semi-supervised approach

作者：

Highlights：

• Backtranslation and forward-translation improve the low resource machine translation.

• External perturbations to the noisy synthetic data help in converging the model.

• Linguistic variations are tackled via the inclusion of multiple test references.

• The proposed method is competitive with pre-trained models.

摘要

•Backtranslation and forward-translation improve the low resource machine translation.•External perturbations to the noisy synthetic data help in converging the model.•Linguistic variations are tackled via the inclusion of multiple test references.•The proposed method is competitive with pre-trained models.

论文关键词：Semi-supervised machine translation,Unsupervised machine translation,Pretrained multilingual machine translation,Statistical machine translation,Neural machine translation,Low resource language,Automatic scoring,Subjective evaluation

论文评审过程：Received 24 December 2021, Revised 19 May 2022, Accepted 14 July 2022, Available online 21 July 2022, Version of Record 2 August 2022.

论文官网地址：https://doi.org/10.1016/j.eswa.2022.118187