A Sastriya Framework for the Adaptation of the Foundational Principles of Classical Indian Dance and Theatre through AI and Machine Learning

Abstract

This study proposes a novel ??str?ya framework for adapting classical Indian dance and theatre into artificial intelligence (AI), machine learning (ML), and virtual production systems, addressing the urgent need to preserve and recontextualise traditional arts in the digital age. Grounded in Bharata’s N??ya??stra and Abhinavagupta’s Abhinavabh?rat?, the research synthesises textual hermeneutics, parampar? praxis, and technical experimentation through an interdisciplinary methodology. Textual analysis computationally encodes ??stric principles, rasa-bh?va theory, abhinaya codification, and n??ya dharm?/lokadharm? dynamics into machine-readable formats (TEI XML, graph databases) to train AI models. At the same time, ethnographic inquiry draws on a decade of training under ?r? Piy?l Bha???c?rya, incorporating case studies with practitioners to reconcile tacit performance knowledge with algorithmic logic.
Leveraging the author’s dual expertise as a VFX line producer and digital transformation consultant, applied experiments deploy markerless motion capture (Intel RealSense), neural radiance fields (NeRF), and generative AI (GPT-4/RAG) to prototype tools for ??stric-aligned choreography, virtual ma??apas (Unreal Engine), and AI-driven pedagogy. Ethical engineering prioritises cultural fidelity: crowdsourced datasets of mudr?s and karanas mitigate Western-centric biases, while retroreflective costume threads and guru-?i?ya validation councils ensure technologies enhance, rather than erode, traditional aesthetics. To validate this approach, we propose employing dual metrics, comprising primarily ??stric peer review (e.g., abhinaya sequence compliance) followed by biometric audience testing (EEG, gaze tracking)—to quantify emotional resonance (rasa) in digital versus live performances. The intention behind this proposed framework is to offer a bridge between Indological scholarship, performing arts parampar?, and AI engineering, creating a scalable global cultural heritage preservation model by demonstrating how ??stric rigour can guide ethical, technological integration without compromising artistic sanctity. The study also suggests a replicable blueprint to utilise modern technological advancements as a digital upav???, a supportive, non invasive tool, to make tradition and the accelerating techno-cultural shifts go hand in hand.