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@article{190753,
        author = {RAKESH S and ROHAN S GOWDRU and TARUN K V and Ashwini J P},
        title = {Automated Linguistic Analysis and Summarization of Sanskrit Prose Using NLP Technique},
        journal = {International Journal of Innovative Research in Technology},
        year = {2026},
        volume = {12},
        number = {8},
        pages = {4906-4913},
        issn = {2349-6002},
        url = {https://ijirt.org/article?manuscript=190753},
        abstract = {Sanskrit, one of the world’s most ancient classical languages, exhibits highly structured grammatical rules, rich morphological variations, extensive sandhi transformations, and complex compound constructions. While these features contribute to its expressive depth, they also make manual linguistic analysis and comprehension of Sanskrit texts both time-intensive and expertise-dependent. To address this challenge, this paper presents an automated Sanskrit text analysis and summarization framework that leverages Natural Language Processing (NLP) techniques combined with rule-based linguistic models tailored to the structural properties of Sanskrit.The proposed system supports both direct textual input and PDF document processing, enabling large-scale analysis of digitized manuscripts and academic resources. Core linguistic operations—including tokenization, sandhi splitting, morphological parsing, script transliteration between Devanagari and Roman formats, and lexicon-based semantic interpretation using classical Sanskrit dictionaries—are employed to derive accurate grammatical and semantic representations. Based on the extracted linguistic features, the system generates concise and context-preserving summaries in modern languages such as English and Kannada. The system produces comprehensive outputs including word-wise meanings, grammatical annotations, transliteration details, summarized content, and downloadable analysis reports. This work contributes to the digital preservation, accessibility, and computational understanding of Sanskrit literature, offering a practical tool for scholars, students, researchers, and digital humanities initiatives.},
        keywords = {Sanskrit Text Analysis; Sanskrit Summarization; Natural Language Processing; Sandhi Splitting; Morphological Analysis; Transliteration; Digital Humanities; Rule-Based NLP; Classical Language Processing},
        month = {January},
        }