Comprehensive Analysis of Sanskrit Text: Lexical Processing

Sanskrit is one of the oldest languages in human civilization, holds immense historical, literary, and philosophical significance. However, due to its complexity and limited accessibility in the modern digital landscape, there is a growing need for tools that facilitate its understanding and utilization. This article aims to bridge this gap by developing a comprehensive Sanskrit text summarization and translation system using Natural Language Processing (NLP) techniques. The system follows a structured three-phase approach to process Sanskrit text efficiently. Initially, the input Sanskrit text is translated into English text using the Google Translate API, ensuring that the content is accessible to a broader audience. Once translated, the English text undergoes an advanced summarization process utilizing the Latent Semantic Analysis (LSA) algorithm from the Sumy library, which extracts the most relevant sentences while retaining the original meaning. This summarized content is then translated back into Sanskrit, providing a concise and refined version of the original text while preserving its essence. The entire process is seamlessly integrated into a user-friendly graphical interface developed using Tkinter, which allows users to input, process, and retrieve results efficiently. The system leverages asynchronous programming to enhance performance, ensuring that translations and summarizations are executed swiftly. By incorporating state-of-the-art NLP methodologies, it significantly contributes to the field of computational linguistics, particularly in Sanskrit language processing. The proposed methodology is not only aids researchers, students, and linguists in analyzing Sanskrit texts but also serves as a foundational tool for future advancements in automated Sanskrit text comprehension. The proposed ideology has the potential to facilitate the preservation and dissemination of Sanskrit literature by making it more accessible in the digital era, thereby fostering continued interest and scholarly exploration in the domain of classical languages.

Authors

Publication Details

Journal
International Journal For Multidisciplinary Research
Published
2025-04-03
DOI
https://doi.org/10.36948/ijfmr.2025.v07i02.40510
Primary Topic
Natural Language Processing Techniques
Type
article
Field-Weighted Citation Impact
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article

Comprehensive Analysis of Sanskrit Text: Lexical Processing

M. Sujatha, Kalidhasan Ramesh, Gaurav Kumar
International Journal For Multidisciplinary Research
Natural Language Processing Techniques
article

Comprehensive Analysis of Sanskrit Text: Lexical Processing

M. Sujatha, Kalidhasan Ramesh, Gaurav Kumar
article en

Abstract

Sanskrit is one of the oldest languages in human civilization, holds immense historical, literary, and philosophical significance. However, due to its complexity and limited accessibility in the modern digital landscape, there is a growing need for tools that facilitate its understanding and utilization. This article aims to bridge this gap by developing a comprehensive Sanskrit text summarization and translation system using Natural Language Processing (NLP) techniques. The system follows a structured three-phase approach to process Sanskrit text efficiently. Initially, the input Sanskrit text is translated into English text using the Google Translate API, ensuring that the content is accessible to a broader audience. Once translated, the English text undergoes an advanced summarization process utilizing the Latent Semantic Analysis (LSA) algorithm from the Sumy library, which extracts the most relevant sentences while retaining the original meaning. This summarized content is then translated back into Sanskrit, providing a concise and refined version of the original text while preserving its essence. The entire process is seamlessly integrated into a user-friendly graphical interface developed using Tkinter, which allows users to input, process, and retrieve results efficiently. The system leverages asynchronous programming to enhance performance, ensuring that translations and summarizations are executed swiftly. By incorporating state-of-the-art NLP methodologies, it significantly contributes to the field of computational linguistics, particularly in Sanskrit language processing. The proposed methodology is not only aids researchers, students, and linguists in analyzing Sanskrit texts but also serves as a foundational tool for future advancements in automated Sanskrit text comprehension. The proposed ideology has the potential to facilitate the preservation and dissemination of Sanskrit literature by making it more accessible in the digital era, thereby fostering continued interest and scholarly exploration in the domain of classical languages.

International Journal For Multidisciplinary ResearchVol. 7(2)
Openalex Percentile: Top 97%
Natural Language Processing Techniques
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