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Significant Enhancements in Machine Translation by Various Deep Learning Approaches

A new and transforming technology for natural language processing and speech processing is deep learning. Deep learning extends various operative ways to train computer systems for learning and it gives significant advances for that. If the right system or architecture is developed with deep learning methods then the systems can automatically learn from data itself without the requirement of designing it overtly. This technique of machine learning changes the perspective of addressing natural language and speech technologies considerably.

Deep learning was first acquainting with Machine Translation in the standard statistical systems. This paper addresses the progress of introduction of deep learning in machine translation. It describes and includes all the topics like integrating deep learning in statistical machine translation, developing end-to-end neural machine translation systems, introducing deep learning in machine translation evaluation. Several research directions are drawn in terms of how deep learning can influence machine translation.

Author(s): Alpana Upadhyay

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Abstracted/Indexed in

  • Index Copernicus
  • Genamics JournalSeek
  • CiteFactor
  • Open Academic Journals Index (OAJI)
  • Directory of Research Journal Indexing (DRJI)
  • Jour Informatics
  • CiteSeerx
  • Journal