MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043221 A) filed by Sr University, Warangal, Telangana, on April 4, for 'a deep learning-based system for automated narrative structure identification and cultural motif extraction in folk tales and oral literature.'
Inventor(s) include Dr. Vahini Billu.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "This invention offers a systematic approach to the study and analysis of folk tales and other forms of oral literature with an emphasis on narrative pattern and motif recognition. The stories and narratives of folk and oral tradition capture the collective knowledge, values and culture of a community, but analysis of these narratives is often reliant on human interpretation, which is time consuming and dependent on source access. The invention offers a structured approach to the collection, analysis and recording of these narratives to facilitate a better understanding of narrative traditions. The system supports the gathering and classification of folk narratives from multiple sources, and their analysis through narrative segmentation and categorization into thematic groups. This allows for the recognition of common plot lines, character archetypes, narrative morals, and culturally important symbols that reflect the social and cultural environments in which these narratives emerged. It also facilitates cross-regional and cross-linguistic study, and promotes interdisciplinary research in literature, folklore and cultural studies. This invention is especially beneficial for academics, educators, students, translators and cultural archivists working on preserving and understanding traditional knowledge systems. The invention of a structured method for recording and analyzing folk narratives helps preserve oral traditions and maintain the importance of folk narratives in literary and cultural studies today. Keywords Deep learning, narrative structure analysis, cultural motif extraction, folk tales, oral literature, natural language processing."
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