A Machine-Learning Framework for Hybrid Machine Translation

Author(s):  
Christian Federmann
Author(s):  
José R. Navarro ◽  
Jorge González ◽  
David Picó ◽  
Francisco Casacuberta ◽  
Joan M. de Val ◽  
...  

2020 ◽  
Vol 184 ◽  
pp. 01061
Author(s):  
Anusha Anugu ◽  
Gajula Ramesh

Machine translation has gradually developed in past 1940’s.It has gained more and more attention because of effective and efficient nature. As it makes the translation automatically without the involvement of human efforts. The distinct models of machine translation along with “Neural Machine Translation (NMT)” is summarized in this paper. Researchers have previously done lots of work on Machine Translation techniques and their evaluation techniques. Thus, we want to demonstrate an analysis of the existing techniques for machine translation including Neural Machine translation, their differences and the translation tools associated with them. Now-a-days the combination of two Machine Translation systems has the full advantage of using features from both the systems which attracts in the domain of natural language processing. So, the paper also includes the literature survey of the Hybrid Machine Translation (HMT).


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