Machine Translation Using Deep Learning : A Survey

Authors

  • Janhavi R. Chaudhary  M. E. Student (Information Technology Department), L. D. College of Engineering, Gujarat Technological University, Ahmedabad, Gujarat, India
  • Ankit C. Patel  Assistant Professor (Information Technology Department), L. D. College of Engineering, Gujarat Technological University, Ahmedabad, Gujarat, India

Keywords:

Machine Translation, Neural Networks, Neural Machine Translation, Deep Learning

Abstract

Machine Translation using Deep Learning (Neural Machine Translation) is a newly proposed approach to machine translation. The term Machine Translation is used in the sense of translation of one language to another, with no human improvement. It can also be referred to as automated translation. Unlike the traditional statistical machine translation, the neural machine translation aims at building a single neural network that can be jointly tuned to maximize the translation performance. This survey reveals the information about Deep Neural Network (DNN) and concept of deep learning in field of natural language processing i.e. machine translation. It is better to use Recurrent Neural Network(RNN) in Machine Translation. This paper studies various techniques used to train RNN for various language corpuses. RNN structure is very complicated and to train a large corpus is also a time-consuming task. Hence, a powerful hardware support (Graphics Processing Unit) is required. GPU improves the system performance by decreasing training time period.

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Published

2018-01-20

Issue

Section

Research Articles

How to Cite

[1]
Janhavi R. Chaudhary, Ankit C. Patel, " Machine Translation Using Deep Learning : A Survey, International Journal of Scientific Research in Science, Engineering and Technology(IJSRSET), Print ISSN : 2395-1990, Online ISSN : 2394-4099, Volume 4, Issue 2, pp.145-150, January-February-2018.