AI-Driven Personalized Multisensory Design of Cultural Heritage: A Case Study of Kunqu Opera
Open Access
Article
Conference Proceedings
Authors: Tián Céng, Jie Zhou
Abstract: With the evolution of global cultural consumption habits, the influence of traditional cultural heritage in contemporary society has gradually diminished. While Kunqu opera is highly regarded for its profound cultural value, its international influence remains limited due to changes in modern cultural consumption habits, language barriers, and the constraints of traditional dissemination methods. To enhance the appeal and impact of traditional culture in modern society, this study takes Kunqu opera, a Chinese intangible cultural heritage, as a case study and explores AI-driven personalized multisensory design strategies. By integrating artificial intelligence technologies, the study aims to create multisensory interactive experiences that engage users’ visual and auditory senses, enabling them to perceive the charm of Kunqu opera, stimulate emotional resonance, and enhance the effectiveness of personalized cultural transmission.This paper proposes a multi-layered design framework that encompasses user data analysis, personalized customization, and multisensory content generation. The study employs AI to deeply analyze and generate the artistic elements and cultural connotations of Kunqu opera. In an innovative approach, it presents Kunqu stories in the form of an animated audio comic, using popular music to express the opera's melodious and delicate vocal style and elegant poetry, while employing a fresh comic style to depict the intricate designs of Kunqu costumes, such as flowing sleeves, fans, and detailed makeup. This transformation of Kunqu's classic performances into dynamic audio-visual experiences allows users to engage interactively and appreciate the opera’s unique charm. On the visual front, generative adversarial networks (GANs) are used to reconstruct Kunqu costumes, stage settings, and performance actions; on the auditory front, deep learning algorithms are applied to perform style transfer and synthesis of traditional singing and music.This research aims to provide new insights for the protection and dissemination of cultural heritage through the AI-driven recreation of Kunqu opera, ultimately enhancing its international recognition and acceptance.
Keywords: Kunqu opera, Artificial intelligence, Multisensory experience, Audiobook comics, Personalized design
DOI: 10.54941/ahfe1006060
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