In this section, we describe the data augmentation methods we use to increase the amount of training data in order to make our NMT systems suffer less from the low-resourced situation in Japanese INLINEFORM0 Vietnamese translation. Back Translation
One of the approaches to leverage the monolingual data is to use a machine translation system to translate those data in order to create a synthetic parallel data. Normally, the monolingual data in the target language is translated, thus the name of the method: Back Translation BIBREF11 . Mix-Source Approach
Another data augmentation method considered useful in this low-resourced setting is the mix-source method BIBREF12 . 
 Question: what methods were used to reduce data sparsity effects?
Back Translation Mix-Source Approach