Natural Language Processing in Vedic Science: A Comprehensive Review and AI-based Framework for Knowledge Extraction
Keywords:
Artificial intelligence, Computational linguistics, Deep learning, Knowledge graph, Machine learning, Natural language processing, Sanskrit, Semantic analysis, Vedic scienceAbstract
The Vedas represent one of the oldest repositories of human knowledge, encompassing diverse domains such as philosophy, medicine, astronomy, mathematics, linguistics, ethics, and spirituality. Composed in Vedic Sanskrit and preserved primarily through oral traditions, these texts possess complex grammatical structures, rich morphology, and profound semantic depth that make computational interpretation a challenging task. Recent advances in artificial intelligence (AI) and Natural Language Processing (NLP) have opened new avenues for the systematic analysis, preservation, and interpretation of ancient textual resources. Modern NLP techniques, including machine learning, deep learning, transformer-based language models, semantic parsing, dependency analysis, and knowledge graph construction, provide powerful tools for extracting structured knowledge from unstructured Sanskrit texts. This paper presents a comprehensive review of NLP applications in Vedic science and examines the evolution of computational approaches for Sanskrit language processing. It discusses the linguistic characteristics of Vedic Sanskrit, existing computational resources, and the major challenges associated with digitization, morphological analysis, semantic interpretation, and multilingual translation. Furthermore, the paper proposes a conceptual AI-driven framework integrating corpus creation, preprocessing, linguistic analysis, semantic modeling, ontology construction, and intelligent knowledge retrieval. The proposed framework aims to preserve the authenticity of Vedic literature while improving accessibility for researchers, educators, and interdisciplinary scholars. The study concludes that the convergence of NLP and Vedic science has the potential to revolutionize digital humanities by enabling semantic search, intelligent question-answering, automated annotation, and knowledge discovery from ancient Indian scriptures.
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