Malayalam Error Sentence Detection using Deep Learning with RNN-LSTM
Supriya L P1, Chinchu M S2

1Supriya L P, Assistant Professor, Department of Computer Science & Engineering, Sree Buddha College of Engineering, Pathanamthitta (Kerala), India.
2Chinchu M S, Research Scholar, Department of Computer Science & Engineering, Anna University, Chennai (Tamil Nadu), India.
Manuscript received on 22 August 2019 | Revised Manuscript received on 03 September 2019 | Manuscript Published on 16 September 2019 | PP: 852-855 | Volume-8 Issue-2S6 July 2019 | Retrieval Number: B11580782S619/2019©BEIESP | DOI: 10.35940/ijrte.B1158.0782S619
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Abstract: 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.
Keywords: Deep Learning, Natural Language Processing, RNN, RNN-LSTM.
Scope of the Article: Deep Learning