Synthetic Data for Neural Machine Translation of Spoken-Dialects
Table 2: Translation performances using BLEU on LEV-ENG-Test for using Bivec vs. word alignment
['System', 'Data Size', 'B LEV-ENG-Test']
We then generate 50K sentences from Arabic-English Subtitles data with bilingual embedding (Gen-Bivec) and without it (Gen-Align). When we are not using Bivec, we just use the word alignment information on the Arabic-English parallel corpus to get the mapping between the words. The result shows that using alignment information is better than using Bivec in this case. It worth noting that using Bivec may be handy if the data is comparable data. In the rest of this work we used word alignment information since it yields better performance.