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Deep learning based spell checker for Malayalam language

Publication Type : Conference Paper

Publisher : Journal of Intelligent and Fuzzy Systems

Source : Journal of Intelligent and Fuzzy Systems, IOS Press, Volume 34, Number 3, p.1427-1434 (2018)

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Keywords : Deep learning, Detection accuracy, Dictionary-based, English languages, Error correction, Error detection, Indian languages, Long short-term memory, Malayalams, Natural language processing systems, spell checker, Spell-checking, Traditional approaches

Campus : Coimbatore

School : School of Engineering

Center : Computational Engineering and Networking

Department : Electronics and Communication

Year : 2018

Abstract : Spell checking plays an important role in conveying correct information and hence helps in clear communication. Spell checkers for English language are well established. But in case of Indian languages, especially Malayalam lacks a well developed spell checker. The spell checkers that currently exist for Indian languages are based on traditional approaches such as rule based or dictionary based. The rich morphological nature of Malayalam makes spell checking a difficult task. The proposed work is a novel attempt and first of its kind that focuses on implementing a spell checker for Malayalam using deep learning. The spell checker comprises of two processes: error detection and error correction. The error detection section employs a LSTM based neural network which is trained to identify the misspelled words and the position where the error has occurred. The error detection accuracy is measured using the F1 score. Error correction is achieved by the selecting the most probable word from the candidate word suggestions. © 2018 - IOS Press and the authors. All rights reserved.

Cite this Research Publication : S. Sooraj, Manjusha, K., M. Kumar, A., and Dr. Soman K. P., “Deep learning based spell checker for Malayalam language”, in Journal of Intelligent and Fuzzy Systems, 2018, vol. 34, pp. 1427-1434.

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