Research Article
NLP and OCR based Automatic Answer Script Evaluation System
|
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
|
| Volume 186 - Issue 42 |
| Published: September 2024 |
| Authors: Pranav Deepak, R. Rohan, R. Rohith, Roopa R. |
10.5120/ijca2024924038
|
Pranav Deepak, R. Rohan, R. Rohith, Roopa R. . NLP and OCR based Automatic Answer Script Evaluation System. International Journal of Computer Applications. 186, 42 (September 2024), 22-27. DOI=10.5120/ijca2024924038
@article{ 10.5120/ijca2024924038,
author = { Pranav Deepak,R. Rohan,R. Rohith,Roopa R. },
title = { NLP and OCR based Automatic Answer Script Evaluation System },
journal = { International Journal of Computer Applications },
year = { 2024 },
volume = { 186 },
number = { 42 },
pages = { 22-27 },
doi = { 10.5120/ijca2024924038 },
publisher = { Foundation of Computer Science (FCS), NY, USA }
}
%0 Journal Article
%D 2024
%A Pranav Deepak
%A R. Rohan
%A R. Rohith
%A Roopa R.
%T NLP and OCR based Automatic Answer Script Evaluation System%T
%J International Journal of Computer Applications
%V 186
%N 42
%P 22-27
%R 10.5120/ijca2024924038
%I Foundation of Computer Science (FCS), NY, USA
Abstract
Evaluation of answer scripts is a tedious laborious process in the education domain. Proper solution is proposed in this paper using two different state of art technologies i.e., Natural Language Processing (NLP) and Optical Character Recognition (OCR). To develop the Automatic Answer Script Evaluation System. The system is intended to simplify grading by automatic the scoring of written responses in a consistent and accurate way. The NLP portion of the system is responsible for understanding the semantic purposes in textual content of answer scripts. It uses state-of-the-art language models to assess and infer the context, coherence, and entailment properties of the generated text answers. Using NLP to understand text, the system can check not only for correct grammar but also gauge how deeply a particular concept is understood.
References
- A. Rokade, B. Patil, S. Rajani, S. Revandkar, and R. Shedge, "Automated Grading System Using Natural Language Processing," in 2018 Second International Conference on Inventive Communication and Computational Technologies (ICICCT), Coimbatore, India, 2018, pp. 1123-1127, doi: 10.1109/ICICCT.2018.8473170.
- V.S. Sadanand, K.R. Guruvyas, P.P. Patil, J. Janardhan Acharya, and S. Gunakimath Suryakanth, "An automated essay evaluation system using natural language processing and sentiment analysis," International Journal of Electrical and Computer Engineering (IJECE), 2022.
- V. Kumari, P. Godbole, and Y. Sharma, "Automatic Subjective Answer Evaluation," 2023, doi: 10.5220/0011656000003411.
- A.K.R. Maya, J. Nazura, and B.L. Muralidhara, "Recent Trends in Answer Script Evaluation – A Literature Survey," 2023, doi: 10.2991/ahis.k.210913.014.
- Prof. S.P. Raut, S.D. Chaudhari, V.B. Waghole, P.U. Jadhav, and A.B. Saste, "Automatic Evaluation of Descriptive Answers Using NLP and Machine Learning," 2022, doi: 10.48175/IJARSCT-3030.
- S. K. et al., "Automatic Answer Evaluation Using Deep Learning Algorithms," 2022, doi: 10.31838/ecb/2023.12.s3.039.
- G. Ng'Ochoi, P. Sijimol, and S. Mariam Varghese, "Grading descriptive answer scripts using deep
- learning," International Journal of Innovative Technology and Exploring Engineering, vol. 8, pp. 991-996, 2019.
- V. Lakshmi and V. Ramesh, "Evaluating Student's Descriptive Answers Using Natural Language Processing and Artificial Neural Networks," ISSN: 2320-2882, 2017.
- N. D. Kamraj, "Survey on Techniques used for Evaluation of Exam Answer Papers," 2020.
- M. Sebastian, R. Kunjumon, S. Shaji, and Prof. S. R., "DigiValuate: Answer Sheet Evaluation System using Natural Language Processing," 2021.
- S. Mangesh, P. Maheshwari, and A. Upadhyaya, "Subjective Answer Script Evaluation using Natural Language Processing," 2022.
- V. Tanwar, "Machine Learning based Automatic Answer Checker Imitating Human Way of Answer Checking," INTERNATIONAL JOURNAL OF ENGINEERING RESEARCH & TECHNOLOGY (IJERT), vol. 10, no. 12, December 2021.
- B. S. J. Kapoor, S. M. Nagpure, S. S. Kolhatkar, P. G. Chanore, M. M. Vishwakarma, and R. B. Kokate, "An analysis of automated answer evaluation systems based on machine learning," in 2020 International Conference on Inventive Computation Technologies (ICICT), Feb. 2020, pp. 439–443, doi: 10.1109/ICICT48043.2020.9112429.
- M. M. Rahman and F. H. Siddiqui, "NLP-based Automatic Answer Script Evaluation," 2018.
- D. Lopresti, "Optical character recognition errors and their effects on natural language processing," IJDAR, vol. 12, pp. 141–151, 2009, DOI: 10.1007/s10032-009-0094-8.
Index Terms
Keywords