Bisazza, Arianna

Dhar, Prajit

van Noord, Gertjan

English

This paper describes our submission for the English-Tamil news translation task of WMT-2020. The various techniques and Neural Machine Translation (NMT) models used by our team are presented and discussed, including back-translation, fine-tuning and word dropout. Additionally, our experiments show that using a linguistically motivated subword segmentation technique (Ataman et al., 2017) does not consistently outperform the more widely used, non-linguistically motivated SentencePiece algorithm (Kudo and Richardson, 2018), despite the agglutinative nature of Tamil morphology

ARTS repository - University of Groningen

Linguistically Motivated Subwords for English-Tamil Translation:University of Groningen’s Submission to WMT-2020

https://pure.rug.nl/ws/files/190346763/2020.wmt_1.9.pdf

Linguistically Motivated Subwords for English-Tamil Translation:University of Groningen’s Submission to WMT-2020

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ARTS repository - University of Groningen