Improving the Quality of Neural Machine Translation Through Proper
  Translation of Name Entities
Radhika Sharma Pragya Katyayan Nisheeth Joshi
In this paper, we have shown a method of improving the quality of neural
machine translation by translating/transliterating name entities as a
preprocessing step. Through experiments we have shown the performance gain of
our system. For evaluation we considered three types of name entities viz
person names, location names and organization names. The system was able to
correctly translate mostly all the name entities. For person names the accuracy
was 99.86%, for location names the accuracy was 99.63% and for organization
names the accuracy was 99.05%. Overall, the accuracy of the system was 99.52%