A Study of State-of-the-Art Neural Machine Translation Approaches

Authors(2) :-Mr. Satish Kumar, Dr. Mohammed Asger

Neural Machine Translation (NMT) is a recent advance proposal technique in machine translation. Neural Machine Translation surpassed the results of Statistical Machine Translation. This report discusses some significant works on the recent advances in neural machine translation. The aim of NMT is to build a single neural network that generates maximum translation performance. This report present the overview of neural network, neural language model which include Recurrent Neural Models (RNN) and Neural Machine Translation models which include encoder-decoder approach, attention-based neural machine translation.

Authors and Affiliations

Mr. Satish Kumar
Department of Information Technology, Baba Ghulam Shah Badshah University, Rajouri-185131, (J&K), India
Dr. Mohammed Asger
Department of Computer Sciences, Baba Ghulam Shah Badshah University, Rajouri-185131, (J&K), India

Neural Network, Neural Machine Translation, Back Propagation Training, Refinements, encoder-decoder approach, attention-based model Feedforword approach

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Publication Details

Published in : Volume 4 | Issue 1 | March-April 2018
Date of Publication : 2018-04-25
License:  This work is licensed under a Creative Commons Attribution 4.0 International License.
Page(s) : 135-139
Manuscript Number : CSEIT411822
Publisher : Technoscience Academy

ISSN : 2456-3307

Cite This Article :

Mr. Satish Kumar, Dr. Mohammed Asger, "A Study of State-of-the-Art Neural Machine Translation Approaches", International Journal of Scientific Research in Computer Science, Engineering and Information Technology (IJSRCSEIT), ISSN : 2456-3307, Volume 4, Issue 1, pp.135-139, March-April-2018.
Journal URL : http://ijsrcseit.com/CSEIT411822

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