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MRI India Journals Vol. 6 No. 3_4 (2019): Volume 6 Issue 3&4 2019

ASSAMESE TRANSLATION SYSTEM

Authors

  • Shayanika Hazarika
  • Poonam Suryawanshi
  • Nikita Shinde
  • Monika Dangore

DOI:

https://doi.org/10.65521/mjret.v6i3&4.1132

Keywords:

Recurrent Neural Network Language Model, Translation Model Statistical Machine Learning

Abstract

Automatic Speech Recognition is the method in which speech signals are translated into the related sequence of characters into text (word). The research on speech recognition has been done for many years ago. After a lot of research work we got the idea of RNN (Recurrent Neural Network) algorithm is more effective and helpful algorithm for speech recognition. The Recurrent Neural Network is the type of Neural Network techniques in which we observe the difference of alphabet. The application or purpose of the RNN is to make people comfortable for the use of Hindi, English and Assamese languages. With the help of this research, people can easily understand languages and get its insight. Languages pose different challenges for speech recognition. This paper discusses about the use of RNN and Statistical Machine Translation algorithms that can be used for translation systems.

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Published

2019-10-01

How to Cite

Hazarika, S., Suryawanshi, P., Shinde, N., & Dangore, M. (2019). ASSAMESE TRANSLATION SYSTEM. Multidisciplinary Journal of Research in Engineering and Technology, 6(3_4), 25–30. https://doi.org/10.65521/mjret.v6i3&4.1132

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