A Framework for Grammatical Error Detection and Correction System for Punjabi Language Using Stochastic Approach

被引:0
|
作者
Jindal, L. [1 ]
Singh, H. [2 ]
Sharma, S. K. [3 ]
机构
[1] SBBS Univ, Jalandhar, Punjab, India
[2] SBBS Univ, Dept Comp Sci & Engn, Jalandhar, Punjab, India
[3] DAV Univ, Dept Comp Sci & Applicat, Jalandhar, Punjab, India
关键词
Punjabi GEC; syntactic analyzer; Grammar checker; HMM; stochastic;
D O I
10.4108/eai.27-4-2021.169421
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:1 / 7
页数:12
相关论文
共 50 条
  • [41] Automated Grammatical Error Detection for Language Learners, 2nd edition
    Lu, Xiaofei
    COMPUTATIONAL LINGUISTICS, 2015, 41 (01) : 149 - 151
  • [42] Comparison of Grammatical Error Correction Using Back-Translation Models
    Koyama, Aomi
    Hotate, Kengo
    Kaneko, Masahiro
    Komachi, Mamoru
    2021 CONFERENCE OF THE NORTH AMERICAN CHAPTER OF THE ASSOCIATION FOR COMPUTATIONAL LINGUISTICS: HUMAN LANGUAGE TECHNOLOGIES (NAACL-HLT 2021), 2021, : 126 - 135
  • [43] Grammatical Error Analysis Approach in Teaching Polish as a Foreign Language to Ukrainian Learners
    Morska, Liliya
    COGNITIVE STUDIES-ETUDES COGNITIVES, 2022, (22):
  • [44] Word sense disambiguation for punjabi language using overlap based approach
    Rana, Preeti
    Kumar, Parteek
    Advances in Intelligent Systems and Computing, 2015, 320
  • [45] MT error detection and correction by Chinese language learners
    Zhang, Qi
    Osborne, Caitriona
    Moorkens, Joss
    TRANSLATION AND INTERPRETING STUDIES, 2024, 19 (02): : 277 - 301
  • [46] Grammatical versus Spelling Error Correction: An Investigation into the Responsiveness of Transformer-Based Language Models Using BART and MarianMT
    Raju, Rohit
    Pati, Peeta Basa
    Gandheesh, Sa
    Sannala, Gayatri Sanjana
    Suriya, Ks
    JOURNAL OF INFORMATION & KNOWLEDGE MANAGEMENT, 2024, 23 (03)
  • [47] Chinese Grammatical Error Detection Using Adversarial ELECTRA Transformers
    Lee, Lung-Hao
    Hung, Man-Chen
    Chen, Chao-Yi
    Chen, Rou-An
    Tseng, Yuen-Hsien
    29TH INTERNATIONAL CONFERENCE ON COMPUTERS IN EDUCATION (ICCE 2021), VOL I, 2021, : 111 - 113
  • [48] Design for Emotion Detection of Punjabi Text using Hybrid Approach
    Grover, Sheeba
    Verma, Amandeep
    2016 INTERNATIONAL CONFERENCE ON INVENTIVE COMPUTATION TECHNOLOGIES (ICICT), VOL 2, 2016, : 240 - 245
  • [49] Detection of Punjabi Newspaper Articles Using a Deep Learning Approach
    Kumar, Atul
    Lehal, Gurpreet Singh
    Lecture Notes in Electrical Engineering, 2024, 1115 : 409 - 418
  • [50] Error Correction and Detection for Computing Memories Using System Side Information
    Schoeny, Clayton
    Alam, Irina
    Gottscho, Mark
    Gupta, Puneet
    Dolecek, Lara
    2018 IEEE INFORMATION THEORY WORKSHOP (ITW), 2018, : 405 - 409