Tamil Sangam literature, composed over two millennia ago, forms a foundational corpus of Tamil cultural and literary heritage. However, challenges such as linguistic complexity, manuscript preservation, and limited accessibility hinder its wider appreciation. This article explores how Artificial Intelligence (AI) technologies—including digitization, natural language processing, and machine translation—can support the preservation, analysis, and dissemination of Sangam texts. By integrating AI with traditional scholarship, this study highlights the transformative potential to deepen understanding and promote Tamil Sangam literature globally.
This research paper evaluates the lifestyle and position of modern human society within the context of contemporary globalization through comprehensive anthropological and sociological theories, based on the classical and ethical literary backgrounds of ancient Tamils. It deeply analyzes the humanistic thoughts embedded in Tolkappiyar’s philosophical classification, Sangam era Purananuru poems, and the secular, universal values of Thirukkural. Furthermore, the Marxist humanistic trends of 20th-century social reformer A. Madhaviah and revolutionary poet Bharathidasan are compared with contemporary modern poetry (Pudukavithai).
The paper discusses the shifts in family structures and social relationships within today's money-centric society against the backdrop of Lewis Morgan's property rights theory, Lévi-Strauss's structuralism, and postmodern moral decay. Finally, policy guidelines are presented regarding the essential role of humanistic education systems—ranging from John Amos Comenius to contemporary international journals—in restoring humanity eroded by modern mechanization, as well as the responsibilities of social institutions in disaster and environmental management.
This study proposes the development of a novel web-based platform leveraging advanced Natural Language Processing (NLP) techniques to address critical needs in Tamil language processing. The platform aims to provide automated solutions for identifying and rectifying spelling and grammar errors, performing contextual text summarization, and enabling real-time speech-to-text transcription of spoken Tamil. While the ultimate objective is a comprehensive user-facing platform, the primary research focus is on the design, development, and implementation of robust underlying machine learning models specifically tailored for the intricate nuances and unique grammatical structures of the Tamil language. The envisioned functionalities include a context-aware spell-checking tool, a sophisticated grammar correction module, an intelligent summarization component capable of condensing text while preserving semantic integrity, and an accurate real-time transcription engine. By tackling the inherent complexities of Tamil, this research seeks to significantly expand the landscape of available language processing tools and empower users with enhanced linguistic accuracy and efficiency.