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State of the Art and Emerging Trends in Indian Languages' Question-Answering Systems: An Overview

by Mamta S. Bendale, Rupali H. Patil, Bhausaheb V. Pawar
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International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 187 - Number 15
Year of Publication: 2025
Authors: Mamta S. Bendale, Rupali H. Patil, Bhausaheb V. Pawar
10.5120/ijca2025925185

Mamta S. Bendale, Rupali H. Patil, Bhausaheb V. Pawar . State of the Art and Emerging Trends in Indian Languages' Question-Answering Systems: An Overview. International Journal of Computer Applications. 187, 15 ( Jun 2025), 49-60. DOI=10.5120/ijca2025925185

@article{ 10.5120/ijca2025925185,
author = { Mamta S. Bendale, Rupali H. Patil, Bhausaheb V. Pawar },
title = { State of the Art and Emerging Trends in Indian Languages' Question-Answering Systems: An Overview },
journal = { International Journal of Computer Applications },
issue_date = { Jun 2025 },
volume = { 187 },
number = { 15 },
month = { Jun },
year = { 2025 },
issn = { 0975-8887 },
pages = { 49-60 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume187/number15/state-of-the-art-and-emerging-trends-in-indian-languages-question-answering-systems-an-overview/ },
doi = { 10.5120/ijca2025925185 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2025-06-26T19:04:51.888444+05:30
%A Mamta S. Bendale
%A Rupali H. Patil
%A Bhausaheb V. Pawar
%T State of the Art and Emerging Trends in Indian Languages' Question-Answering Systems: An Overview
%J International Journal of Computer Applications
%@ 0975-8887
%V 187
%N 15
%P 49-60
%D 2025
%I Foundation of Computer Science (FCS), NY, USA
Abstract

As digital technologies continue to evolve, the demand for effective natural language processing (NLP) systems tailored to Indian languages has grown significantly. Most of the researchers has been concentrated on languages with rich digital resources, frequently failing to acknowledge the Indian subcontinent's linguistic diversity. This review paper seeks to address this deficiency by offering a thorough summary of the progress and improvements in Question Answering Systems(QASs), particularly for Indian languages. With 22 official languages recognized under the eighth schedule of the Indian Constitution, India has a vast linguistic variety. QASs are an essential part of NLP that try to understand user inquiries and provide human-like answers. In this study, an overview of QAS research for several Indian languages is presented. The analysis and outcomes regarding Categories of Indian Languages, Necessity of Indian Languages' Question-Answering Systems, applications of QAS and approaches of QAS’s are reported. This review distinguishes itself from previously available reviews by including languages such as Odia, Sanskrit, Kannada, Assamese, and others. The study also highlights that BERT and SVM are the most used models for developing QAS in various Indian languages. All conclusions are drawn based on a review of the literature.

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Index Terms

Computer Science
Information Sciences

Keywords

Automatic Question Answering Categorization of Indian Languages Applications and Approaches of Question Answering System Indian Languages in Question Answering System

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