A novel Sentimental Analysis framework using Gated Recurrent Units for Text Transliteration

Transliteration is the process of converting the characters of one writing system into the corresponding characters of another writing system. It is often used to represent the sounds of words from one language using the characters of another language. There were multiple Artificial Intelligent techniques which were extensively used for sentimental analysis. Natural Language Processing (NLP) is one of the effective ways for sentimental analysis that generates the language interpretation. This enables the way for enabling transliteration from one language to another or a combination. This article proposes a way of deploying a Gated Recurrent Unit (GRU) which is a type of Recurrent Neural Network (RNN) architecture that is commonly used in NLP and sequence-to-sequence learning tasks.