Research Article
A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach
@ARTICLE{10.4108/eai.27-4-2021.169421, author={L. Jindal and H. Singh and S. K. Sharma}, title={A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach}, journal={EAI Endorsed Transactions on Scalable Information Systems}, volume={8}, number={32}, publisher={EAI}, journal_a={SIS}, year={2021}, month={4}, keywords={Punjabi GEC, syntactic analyzer, Grammar checker, HMM, stochastic}, doi={10.4108/eai.27-4-2021.169421} }- L. Jindal
H. Singh
S. K. Sharma
Year: 2021
A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach
SIS
EAI
DOI: 10.4108/eai.27-4-2021.169421
Abstract
INTRODUCTION: In this modern era of internet and technology natural language processing task has emerged as one of the major research area in computer science. Grammatical error detection and correction system assists to detect and correct syntactic errors present in written text. OBJECTIVES: In this research article, author investigate the applicability of stochastic approach for the development of grammatical error detection and correction system for Punjabi language. METHOD: Author used corpus based stochastic approach to developed the system. The corpus used was taken from Indian language corpora initiative. RESULTS: On testing, the developed system shows a precision as 82.5%, recall as 89% .and f-measure as 85%. The results of the proposed system outperform the existing rule based system that shows precision of 76.79%, recall of 87.08%, and F-measure of 81.61%. CONCLUSION: author concluded that for syntax analysis stochastic approach can perform better than rule based approach.
Copyright © 2021 L. Jindal et al., licensed to EAI. This is an open access article distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/3.0/), which permits unlimited use, distribution and reproduction in any medium so long as the original work is properly cited.