Multilingual NLP and Voice-Based System for Predicting Scheme Eligibility and Providing Guidance

J. Angelin Jeba, S. Rubin Bose, O. Jeba Singh, R. Regin, R. Jesfer, Jouma Ali Al-Mohamad Department of Electronics and Communication Engineering, S.A. Engineering College, Chennai, Tamil Nadu, India. School of Computer Science and Engineering, SRM Institute of Science and Technology, Ramapuram, Chennai, Tamil Nadu, India. Centre for Academic Research, Alliance University, Bengaluru, Karnataka, India. Department of Computer Science and Engineering, Dhaanish Ahmed College of Engineering, Chennai, Tamil Nadu, India. Department of Computer and Mobile Communications Engineering, Faculty of Information Engineering, Al-Shahbaa Private University, Aleppo, Syria.

Abstract: Citizens have a problem accessing government programs because of the dispersion of information, lack of clarity on the application eligibility, and inadequate assistance when applying. Such issues often deny beneficiaries the support and opportunities to which they are entitled. To address this problem, this paper proposes a Personalized Government Scheme Assistance System that provides users with customized advice and step-by-step guidance based on their demographic, occupational, and financial profiles. The proposed system is designed to provide detailed guidance, unlike the available solutions, which only identify eligibility; it elaborates on the required documents, eligibility criteria, and application procedures. It has an NLP-driven chatbot that provides a more natural, interactive experience, and the multilingual option makes it more inclusive for users with different linguistic backgrounds. Moreover, the inclusion of a voice-based chatbot increases accessibility for those with low literacy or digital skills. The platform focuses on a clear, viable UI/UX design that is understandable, easy to use, and simplified for citizens from diverse socio-economic groups. Through a blend of personalization, conversational AI, and inclusive design, such a system will help bridge the knowledge gap between government initiatives and their accessibility to citizens, increase awareness, streamline the application process, and boost citizen participation in government benefit programs. In the end, the work will help promote inclusive socio-economic growth by increasing the accessibility, actionability, and inclusivity of government services for everyone.

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Keywords: Personalized Recommendation; NLP-Powered Chatbot; Multilingual Support; Voice-Based Chatbot; UI/UX Design; Artificial Intelligence; Natural Language Processing; Large Language Models.

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Received on: 09/06/2025Revised on: 28/07/2025Accepted on: 25/08/2025Published on: 01/03/2026

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