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Stream/Area:
-
Subject:
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Paper ID:
IJSREM62892
Volume:
10 |
5 |
May 2026
Pages:
1-8
Publication Frequency:
Monthly (12 issues per year)
License:International Journal of Scientific Research in Engineering and Management follows the Creative Commons Attribution 4.0 (CC BY 4.0) License, allowing free use and distribution with proper attribution.

computer science and engineering
smt indira gandhi college of engineering

computer science and engineering
smt indira gandhi college of engineering

computer science and engineering
smt indira gandhi college of engineering

computer science and engineering
smt indira gandhi college of engineering

computer science and engineering
smt indira gandhi college of engineering
The Veda Voice project is an AI-based Ayurvedic assistant that provides natural healthcare guidance using NLP and voice recognition. It bridges traditional Ayurveda with modern AI, allowing users to input symptoms and receive herbal remedies, diet plans, and lifestyle suggestions. The system improves accessibility and promotes preventive healthcare. The oral tradition of Vedic chanting is one of the oldest knowledge transmission systems. However, its preservation faces challenges due to modernization and declining practitioners. This paper presents Veda Voice, an Artificial Intelligence-based system designed to recognize and analyze Vedic chants using speech processing and deep learning techniques.
KEYWORDS
· In conclusion, the Veda Voice system effectively utilizes modern web technologies and AI-based processing to build a comprehensive, efficient, and user-friendly digital healthcare platform. By integrating features such as chatbot interaction, Ayurvedic knowledge access, quiz-based learning, and user profile management into a single interface, it simplifies the process of accessing traditional healthcare guidance and improves overall user experience. · The intuitive design ensures that even non-technical users can easily interact with the system, making Ayurvedic knowledge more accessible to a wider audience. Additionally, the modular architecture of the platform supports scalability and flexibility, allowing future enhancements such as improved AI models, expanded datasets, and advanced personalization features without affecting existing functionality. · Overall, Veda Voice provides a complete and integrated solution that combines traditional Ayurvedic wisdom with modern technology. It supports users in understanding symptoms, exploring remedies, and improving their lifestyle, making it a reliable and future-ready digital health assistant.
[1] K. Hemalatha, G. Vinay, S. Bhavya Sree R, Y. S, and T. K, “Prakriti Bot – Intelligent Prakriti Analysis Chatbot for Personalized Ayurvedic Suggestions,” International Research Journal of Innovations in Engineering and Technology (IRJIET), vol. 9, Special Issue INSPIRE’25, pp. 337–342, Apr. 2025 [2] M. V. Gunaga, M. Manvith, P. Preethesh, S. A. V, and K. Kiran, “Ayurvedic Chatbot,” Journal of Emerging Technologies and Innovative Research (JETIR), vol. 12, no. 7, pp. 802–803, Jul. 2025. [3] S. Mohan Vamsi and S. Noortaj, “Ayurveda Plant Identification and Medicare Chatbot Assistant,” International Journal of Scientific Research in Computer Science, Engineering and Information Technology, vol. 11, no. 7, pp. 576–581, May–Jun. 2025. [4] B. P. S. Chundawat, D. Chouhan, A. Kumar, M. Bhatt, and M. Patel, “Utilizing Chatbots for Individual Prakriti in Ayurveda: A Modern Approach to Personalized Healthcare,” International Advanced Research Journal in Science, Engineering and Technology (IARJSET), vol. 11, Special Issue 2, pp. 68–70, May 2024. [5] Deng, L., Li, J., Huang, J. T., Yao, K., Yu, D., Seide, F., ... Zweig, G. (2013). Recent advances in deep learning for speech research at Microsoft. In 2013 IEEE international conference on acoustics, speech and signal processing (pp. 8604-8608). IEEE. [6]Gopalakrishnan, S., Ganapathy, K., Raghunathan, A., & Muralidharan, V. (2018). Chatbot-based Prakriti evaluation and management in Ayurveda: Design and development. In 2018 IEEE 8th International Advance Computing Conference (IACC) (pp. 392-397). IEEE [7]Menaria, H.K., Nagar, P., Patel, M. (2020). Tweet Sentiment Classification by Semantic and Frequency Base Features Using Hybrid Classifier. In: Luhach, A., Kosa, J., Poonia, R., Gao, XZ., Singh, D. (eds) First International Conference on Sustainable Technologies for Computational Intelligence. Advances in Intelligent Systems and Computing, vol 1045. Springer, Singapore. https://doi.org/10.1007/978-981-15-0029-9_9 [8]Singh, N., Singh, S. P., & Nath, R. (2019). Development and validation of questionnaire for assessment of Prakriti: A preliminary study. AYU (An international quarterly journal of research in Ayurveda), 40(1), 24 [9]D. Kothari, M. Patel and A. K. Sharma, "Implementation of Grey Scale Normalization in Machine Learning & Artificial Intelligence for Bioinformatics using Convolutional Neural Networks," 2021 6th International Conference on Inventive Computation Technologies (ICICT), Coimbatore, India, 2021, pp. 1071- 1074
Publication Date
5/8/2026
Peer Review Type
Double-Blind Peer Review
Review Rounds: 2
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