
Malayalam Error Sentence Detection using Deep Learning with RNN-LSTM
Publication year - 2019
Publication title -
international journal of recent technology and engineering
Language(s) - English
Resource type - Journals
ISSN - 2277-3878
DOI - 10.35940/ijrte.b1158.0782s619
Subject(s) - malayalam , computer science , sentence , recurrent neural network , artificial intelligence , natural language processing , word (group theory) , speech recognition , meaning (existential) , linguistics , artificial neural network , psychology , philosophy , psychotherapist
Malayalam is a difficult Indian language and not easy for foreigners. Even as a mother tongue, you should spend more time learning as a child. In Malayalam, the use of the wrong word in a sentence may change the whole meaning and purpose. Many errors occur during the writing process. It is very difficult to find errors in the Malayalam language, and no one can remove those errors without their linguistic knowledge In this paper, we have proposed the structure of repetitive neural networks using long short-term memory (RNN-LSSTM) to detect Malayalam sentence errors.