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Zero-Shot Language Transfer vs Iterative Back Translation for Unsupervised Machine Translation

2021-03-31 20:47:19
Aviral Joshi, Chengzhi Huang, Har Simrat Singh
arXiv_AI
       
Abstract

This work focuses on comparing different solutions for machine translation on low resource language pairs, namely, with zero-shot transfer learning and unsupervised machine translation. We discuss how the data size affects the performance of both unsupervised MT and transfer learning. Additionally we also look at how the domain of the data affects the result of unsupervised MT. The code to all the experiments performed in this project are accessible on Github.

Abstract (translated)

URL

https://arxiv.org/abs/2104.00106

PDF

https://arxiv.org/pdf/2104.00106.pdf

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