NLP-BASED FOLK STORY DOCUMENTATION SYSTEMS
DOI:
https://doi.org/10.29121/shodhkosh.v6.i5s.2025.6879Keywords:
Cultural Heritage Preservation, Semantic Annotation, Transformer Models, Multilingual Corpus, Knowledge Graph, BER Topic, Ontology Alignment, Digital HumanitiesAbstract [English]
The folk tales are invaluable sources of cultural wisdom, language diversity and collective memory. Much of this intangible heritage is however in danger after the diminishing oral tradition and poor documentation mechanisms. This paper will introduce a NLP-based folk story documentation and preservation framework, which includes the state of the art natural language processing, semantic models as well as ontology-based cultural representations. The suggested pipeline works with multilingual and dialect-containing texts, handling them in a set of computational steps, which are text preprocessing, linguistic analysis, motif discovery, semantic annotation, and the development of the cultural knowledge graphs. Transformer-based models mbERT, IndicBERT and RoBERTa have been fine-tuned on language-specific tasks and BERTopic and TransE embeddings were used to perform thematic clustering and ontology alignment on the CIDOC-CRM schema. The outcomes of the evaluation showed that there were great improvements in linguistic accuracy (F1 = 0.91), motif classification (F1 = 0.83), and topic coherence (CV = 0.74) in comparison to the traditional baselines. The validation of the experts in the field of folklorists and linguists provided a Cultural Authenticity Index (CAI) of 0.87, which validated the interpretive reliability of the system. The acquired body of knowledge can be used to aid semantic querying, comparative motif analysis and cultural pattern recognition and hence convert the archives, which are normally static folklore collections, into smart, interactive ones. It finds applications in the digital heritage management, education, creative storytelling and cross-cultural analytics. Altogether, the framework contributes to a scaled and ethically justified method of the AI-assisted cultural preservation as the linguistic richness and narrative depth of the folk traditions can survive in the digital age.
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Copyright (c) 2025 Richa Srivastava, Ramu K, Ayush Gandhi, Shubhangi S. Shambharkar, Chandrashekhar Ramesh Ramtirthkar, Dr. L. Lakshmanan
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