数智技术介入非物质文化遗产的创新性发展

目前文本生成图像的研究已显示出与普通画家类似的水平,但与艺术家绘画水平相比仍有很大改进空间;艺术家水平的绘画通常将多个意象的特征融合到一个意象中,以表示多层次语义信息。在预实验中,我们证实了这一点,并咨询了3个具有不同艺术欣赏能力的群体的意见,以确定画家和艺术家之间绘画水平的区别。之后,利用这些观点帮助人工智能绘画系统从普通画家水平的图像生成改进为艺术家水平的图像生成。具体来说,提出一种无需任何进一步预训练的、基于文本的多阶段引导方法,帮助扩散模型在生成的图像中向多层次语义表示迈进。实验中的机器和人工评估都验证了所提方法的有效性。此外,与之前单阶段引导方法不同,该方法能够通过控制不同阶段之间的指导步数来控制各个意象特征在绘画中的表现程度。

This study addresses the challenges of the dynamic transmission of intangible cultural heritage (ICH) sports by leveraging digital intelligence technologies to develop an innovative sports tourism app solution. It explores integrated pathways for ICH preservation and transmission through the convergence of “culture, technology, and tourism.” Employing literature review, questionnaire surveys, and architectural design experiments, the research constructs an ICH sports tourism app. Findings indicate that technologies such as AR-based real-world navigation and AI-driven motion capture instruction can overcome the limitations of offline transmission efficiency and fulfill users’ core needs for skill acquisition. The differentiated demands of various user groups necessitate a tiered functional design, integrating technologies like blockchain for rights confirmation and digital twins to establish a closed-loop ecosystem encompassing a knowledge base, instructional system, and commercial empowerment. Interface design, featuring dynamic ICH maps and personalized recommendations, enhances user engagement, while the development of cultural IP expands monetization opportunities. The study demonstrates that a digital intelligence-driven app, through technological integration and demand adaptation, offers an innovative paradigm for the dynamic transmission and industrial transformation of ICH sports.

Against the backdrop of the in-depth integration of culture and tourism, the inheritance and development of intangible cultural heritage (ICH) are embracing new opportunities as well as challenges. As one of the first entries inscribed on the UNESCO Representative List of the Intangible Cultural Heritage of Humanity, the ceramic ICH of Jingdezhen has been incorporated into the key projects of the national cultural digitization strategy, which necessitates breaking its development bottlenecks by virtue of culture-tourism integration and digital technologies. Taking Jingdezhen’s ceramic ICH as the research subject, this paper focuses on the core transformation of ICH from static exhibition to digital-intelligent inheritance. Based on the innovative practices of typical cultural-tourism scenarios such as in Taoxichuan, the Imperial Kiln Museum, Sanbao Village and Letian Market, it analyzes the coordinated development of culture-tourism integration and ceramic ICH, explores the paths and modes of ICH’s digital-intelligent inheritance empowered by digital technologies, and thus provides a reference for the sustainable development of handicraft-based ICH industries.

With the rapid development of digital technology and artificial intelligence (AI), the digital communication of intangible cultural heritage (ICH) has entered a transformative stage.  This study focuses on the case of Yungang Culture—a representative and ideologically rich form of Chinese traditional culture—to explore how AI empowers the effectiveness of digital ICH dissemination.  Drawing on grounded theory and structural equation modeling (SEM), this research constructs and verifies a multidimensional model incorporating content ontology, communication agents, audience characteristics, and environmental context.  A nationwide questionnaire survey (N = 321) was conducted, and SmartPLS and AMOS were used for empirical validation.  Results reveal that audience cognition and understanding significantly mediate the relationship between influencing factors and behavioral engagement.  Among the key variables, content quality and platform authority are shown to have the greatest influence on audience comprehension, while AI-enabled functions—such as personalized recommendation and multimedia adaptation—play an implicit but crucial role in optimizing communication pathways.  The study not only enriches the theoretical landscape of digital cultural communication but also provides practical implications for AI-driven ICH dissemination strategies in China and beyond.

Protecting intangible cultural heritage is of great significance for maintaining the creativity and diversity of human civilization. Through digital management, sustainable development can be achieved. In this paper, a digital resource management model for intangible cultural heritage that integrates artificial intelligence and blockchain technology is proposed. It aims to address the difficulties in preservation, inheritance and verification compared with traditional methods of intangible cultural heritage protection. This model combines blockchain and artificial intelligence technologies. Through blockchain and edge computing networks, it ensures the efficient processing of intangible cultural heritage resource data, as well as its immutability and traceability. Artificial intelligence technology enables functions such as digital restoration, intelligent retrieval, and personalized recommendation of intangible cultural heritage resources. Dynamic management of intangible cultural heritage resources can enhance the efficiency of resource utilization. It is conducive to protect and inherit intangible cultural heritage resources.

The preservation of intangible cultural heritage (ICH) faces significant and multifaceted challenges due to its ephemeral nature, reliance on oral traditions, and contextual embeddedness within lived cultural experiences. Traditional preservation approaches—such as textual documentation, static archiving, and audiovisual recordings—often fall short in capturing the dynamic, embodied, and performative characteristics that define ICH practices. To overcome these limitations, we propose an innovative computational framework that integrates advanced neural representations with structured symbolic logic and contextual grounding mechanisms. We introduce a novel neural-symbolic architecture capable of modeling the fluid, multimodal, and socially constructed nature of intangible cultural knowledge. Our approach includes a culturally informed reasoning strategy that enables the system to align observed cultural signals with both canonical forms and evolving variants within a specific tradition. This is further enhanced by a self-supervised semiotic alignment module, which dynamically adapts through iterative engagement with context-specific cues and emergent performative deviations. By leveraging cutting-edge artificial intelligence, our framework enables the digital preservation, interactive representation, and inclusive transmission of ICH, ensuring its resilience, relevance, and accessibility across generations and communities in a rapidly evolving global landscape.

In view of the current problems of single display form and poor interaction of intangible cultural heritage painting wave, a digital online display system of intangible cultural heritage painting is designed and realized based on mobile augmented reality technology. Taking the intangible cultural heritage protection of Dunhuang murals as an example, the main functional modules of the system cloud and mobile terminal are designed, a fast modeling method based on the combination of 3 D scanning and grid iteration and simplification is proposed, ORB-FV and optical flow tracking algorithm are adopted to realize online image recognition and tracking registration, and the system development is completed based on Unity3D. The test results show that the system not only meets the requirements of the authenticity and fluency of the mobile terminal enhanced display of the intangible cultural heritage products but also realizes the real-time interactive coloring display function after the model enhanced display, which enhances the interest and interactivity of the intangible cultural heritage protection and dissemination. Through the research on the digital display of intangible cultural heritage painting of artificial intelligence technology, and the verification in the experiment, this topic found that the display of intangible cultural heritage painting art in the digital age can present a variety of inheritance methods, which also marks the intangible cultural heritage painting exhibition towards a new direction. Using the cell dynamics model of biomechanics, the impact of digital display on user visual interaction is explored, thereby enhancing the audience’s immersion and understanding of intangible cultural heritage paintings.

Digital preservation and transmission of intangible cultural heritage (ICH) are important in preserving cultural identity in the face of modernization. Virtual Reality (VR) technology offers an effective medium for experiential, interactive presentation of ICH components with new forms of cultural engagement, particularly among younger audiences. Current systems rely heavily on text or 2D media, which have no experiential depth and emotional impact, resulting in less interested audiences and incomplete cultural comprehension. Traditional methods-i.e., photographic documentation, oral recording, and 2 D archiving-cannot capture the performative and spatial nature of ICH practice. The model adopted is based on a VR-based reconstruction system complemented by the Spatio-Temporal Attention Graph Convolutional Network (STAGCN) algorithm that allows realistic simulation of rituals, crafts, and folk arts. This model guarantees dynamic interaction, high-fidelity visualization, and contextual learning. Comparative performance against baseline CNN and LSTM models demonstrates improved performance of STAGCN model of accuracy at 99.2 %, F1-score at 98.5 %, and pointing towards improved feature representation and cultural authenticity. The excellence comes in the form of spatialtemporal consistency and adaptive attention learning, performing significantly better than static models for user immersion, accuracy, and effectiveness in retaining culture.

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The sustainable development of intangible cultural heritage (ICH) faces multiple challenges, including societal structural transformations, intergenerational transmission gaps, and the loss of cultural memory. The rapid advancement of generative artificial intelligence (AI) technologies offers new possibilities for the digital preservation and innovation of ICH. This study leverages generative AI to develop a LoRA model embodying the Blue Clamp-Resist Dyeing style, enabling the digital preservation and innovative reinterpretation of traditional patterns. Additionally, the study integrates these technological achievements into an interactive experience project at the Wenzhou Blue Clamp-Resist Dyeing Museum. Through immersive experiences in pattern generation and dissemination, the project effectively enhances public engagement and cultural identity. The findings reveal that generative AI holds significant potential for promoting the digital transformation, innovative dissemination, and sustainable development of ICH. This study offers a practical approach to the preservation and innovation of intangible cultural heritage. By applying generative artificial intelligence, it further expands the potential for enhancing public engagement and promoting innovative cultural heritage transmission. Additionally, it provides new possibilities for leveraging digital technologies to support the sustainable development of intangible cultural heritage.

Intangible Cultural Heritage (ICH) represents the customers, behaviors, and expressions that have been handed down through the generations, including folklore, performing arts, rituals, languages, and craftsmanship. Unlike tangible heritage, including objects and monuments, ICH is vulnerable to destruction due to globalization, urbanization, and generational gaps. Traditional methods of preservation, such as manual documentation and oral transmission, struggle to adapt to the digital era, leading to the loss of valuable cultural knowledge. Artificial Intelligence (AI) has become a revolutionary instrument for ICH preservation, offering solutions for digital preservation, restoration, and interactive dissemination. To address these issues, this research proposes a Galactic Swarm Optimized Graph Neural Network (GSO-GNN) for ICH’s improved inheritance and protection. The proposed approach begins with comprehensive ICH preservation of data. A pre-processing phase, including data cleaning and noise reduction, ensures the accuracy and consistency of the dataset and then feature extraction was conducted using Principal Component Analysis (PCA). The GNN is then employed to map complex relationships between cultural elements, preserving their contextual significance. To enhance efficiency, GSO is integrated to refine feature selection, improve model accuracy, and optimize computational resources. The findings show that the proposed method outperforms other techniques in terms of the [Formula: see text]1-score (98%), recall (98.48%), accuracy (99%), and precision (98%). Furthermore, AI-driven dissemination significantly enhances accessibility and engagement for global audiences, contributing to cultural sustainability and protection. By efficiently modeling complex cultural relationships and optimizing computational performance, the GSO-GNN platform offers a practical and scalable way to preserve digital heritage.

The protection of intangible cultural heritage (ICH) is not only respect and protection for traditional culture, but also plays a vital role in cultural inheritance, social identity, historical memory, economic development, and innovative vitality. With the rapid advancement of globalization and modernization, ICH is also facing unprecedented challenges. However, the traditional protection of ICH has problems such as focusing on static physical protection, insufficient information storage, limited transmission, insufficient modern transformation and innovation, excessive restoration of traditional elements and conservative protection. In response to the above problems, this paper designs an ICH resource construction system based on artificial intelligence (AI) biological perception. It can perceive ICH data through multimodal biology, store and reproduce it, perform feature analysis based on biological emotions and emotional interactions, capture the inheritance logic and emotional connotation of culture, and drive the digital modeling of ICH resources with intelligent design. Dynamic ICH content can be superimposed on real scenes to facilitate education and dissemination, and personalized ICH story content can be recommended based on user preferences to enhance the display and dissemination capabilities of ICH. The results show that the system uses multimodal perception and stores more than 100,000 ICH data items in four major categories and multiple subcategories, and designs a unique interactive tag cloud for users to choose from. When making recommendations for users, it recommends 200 ICH contents to users from the sorted list simultaneously, and the proportion of users clicking on the recommendations reaches 85%, while also achieving the widespread dissemination of ICH in Asia. Compared with traditional ICH protection, this study has achieved efficient digital storage of ICH content, strong modern conversion, and ease of acceptance by users. The scope of dissemination is also wider. This shows that the use of AI and biosensing technology in ICH protection is effective and can contribute to better preservation, publicity and promotion of ICH.

This study explores the intelligent integration of intangible cultural heritage elements into modern digital design. By utilizing a deep learning model, a system for cultural element extraction and generation is constructed, enabling multi-level feature extraction of traditional designs. Through the application of generative adversarial networks, this model seamlessly blends cultural symbols with contemporary design. Experimental results indicate that the model significantly enhances both the cultural coherence and modern aesthetic adaptability of designs, achieving innovative heritage preservation within a digital context. The findings suggest that, through model optimization and broader application, intangible cultural heritage can achieve sustained dissemination across various digital platforms.

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Digital modeling technology breaks the geographical limitations of traditional intangible cultural heritage (ICH) dissemination, enabling more people to participate in the protection and inheritance of ICH in a more intuitive and vivid way. This study explores the application of digital modeling technology in the digital inheritance of traditional ICH and compares three neural network models—the multi-scale detail perception network (MDPN), DenseNet, and EfficientNet. The results show that the MDPN excels in detail processing and computational efficiency, accurately reconstructing the complex textures and fine patterns in ICH images. When combined with other models, the MDPN provides users with an immersive experience when both viewing and creating ICH. In conclusion, digital modeling technology is becoming an important tool for promoting the widespread dissemination of ICH.

Although there is no distinctive header, this is the abstract. This paper addresses the challenges of low recognition accuracy and weak teaching interaction in the digital preservation of Liaoning's intangible cultural heritage by integrating computer vision and generative AI. This study constructs a parallel architecture combining a multi-scale attention CNN and a domain-adapted Transformer, achieving dynamic alignment of visual and semantic features through mutual information guidance. A sample generation module based on an improved WGAN is designed to triple the sample size of scarce intangible cultural heritage artifacts, such as Fuzhou shadow puppetry. Finally, a three-tiered “cloud-edge-end” digital teaching system is developed, integrating resource libraries, recognition and display, personalized recommendations, and virtual interaction modules. Experiments based on the self-built LNMD-2024 dataset (26,800 samples) demonstrated that the model achieved 92.3% recognition accuracy and 92.1% F1 score, representing improvements of 8.5%-9.2% over traditional methods. The generated sample structure similarity reached 0.89. The system response latency was ≤480ms under 500 concurrent users, and GPU utilization remained stable at 75%. This research provides a technical paradigm for the intelligent inheritance of intangible cultural heritage and has increased user retention by 42%.

With the increasing demand for the protection and dissemination of intangible cultural heritage (ICH), the digitization and innovative redesign of traditional patterns have become important directions for cultural inheritance. This paper proposes a digital art design and intelligent re-creation method for ICH patterns based on the Diffusion Model (DM). First, a database containing 4320 high-resolution ICH patterns is constructed, and semantic correspondence is achieved through feature annotation. Second, an improved Latent Diffusion Model (LDM) is adopted, introducing an attention-guided module and a cultural semantic embedding layer to enhance the model's understanding of the semantic and stylistic features of the patterns. Then, through style transfer and feature fusion algorithms, the diverse generation and innovative re-creation of ICH pattern styles are achieved. Finally, the effectiveness is evaluated using subjective aesthetic evaluation and the Structural Similarity Index (SSIM). The generated patterns achieve a structural fidelity of 0.956, a 12 % improvement in style consistency , and an average user aesthetic score of 1.4 . This study not only verified the feasibility and innovation of the diffusion model in the digital art design of intangible cultural heritage, but also provided a technical path with practical value for the intelligent transmission of cultural heritage.

Given that traditional graph structures make it difficult to capture complex interaction information between entities, this study adopts a hypergraph model to represent multimodal and heterogeneous data, to adapt to the complexity of dragon and lion dance movements. This study proposes a new method based on a hypergraph convolutional network (HGCN) for the inheritance and teaching action evaluation of the intangible cultural heritage of the dragon and lion dance. This method constructs the HGCN model, combined with a self-attention mechanism to accurately evaluate action details and promote its inheritance in the digital age. The results show that the HGCN algorithm incorporating the attention mechanism exhibits excellent performance, the accuracy achieves 0.941, the error rate reduces to 0.333, an evaluation efficiency improved by 400%, and user satisfaction increases to 0.900. These results not only validate the efficiency and accuracy of the model but also demonstrate its potential to improve the teaching and inheritance efficiency of the dragon and lion dance. This study not only provides a new technological means for the digitization of intangible cultural heritage in sports but also opens up new paths for the modern teaching and inheritance of traditional sports projects.

With its unique interactivity, communicative power, and innovativeness, digital art design offers a new pathway for the dissemination of intangible cultural heritage (ICH). As a cutting-edge technology in the field of artificial intelligence, generative AI leverages machine learning algorithms and big data analytics to automatically generate multimodal content such as text, images, audio, and video, thereby greatly enhancing design efficiency. This study examines the characteristics and challenges of digital art design related to ICH, elucidates the fundamental principles and technical features of generative AI, and discusses its application logic and potential scenarios in ICH-focused digital art design. It also identifies the current limitations of generative AI and proposes corresponding solutions, aiming to provide new approaches and methods for ICH transmission and preservation, advance the integration of digital art design with AI technologies, and promote innovative development in the cultural and creative industries related to ICH.

The preservation of intangible cultural heritage (ICH) has gradually shifted to digital innovations in the era of expanding information technologies (IT). This study uses brief video communication to investigate the function of artificial intelligence (AI) in ICH protection. A social networking platform is connected with the AI-driven method. This study comprises instances of short videos and concentrates on essential components like musical instruments and traditional music. Next, the linguistic (text) and visual aspects of the short videos are evaluated using computer vision techniques like You only look once (YOLO) network and natural language processing (NLP) approaches. We use AI-driven analysis to find trends in the data, and we also use qualitative analysis to present it. The random forest (RF) model is developed to assess the heritage transmission level in the videos based on factors like security and cultural importance. The outcomes of the RF model are analyzed in terms of precision, accuracy, and f-measure metrics. Additionally, performance comparisons of the allocation of traditional musical instruments under different production types are carried out, and outcomes are also obtained visually using data visualization tools. This study finally shows how AI can be used to enhance ICH safety through short video communication technology.

As times progress, the systematic protection and innovative development of Intangible Cultural Heritage (ICH) have garnered significant social attention. This study investigates the protection and inheritance strategies for the Jin-style filigree mosaic art, an ICH, in the digital era, addressing the challenges of cultural identity in a rapidly evolving social context. Grounded in schema theory and integrating digital and artificial intelligence technologies, the study devises specific methods for safeguarding and perpetuating this art form. The research team initially examined the historical background, artistic features, and current state of inheritance of the Jin-style filigree mosaic art. Subsequently, they crafted VR/AR encoding plans and validated their efficacy through experimental trials. By surveying 1,138 students from art schools and amassing data on their satisfaction with VR/AR-based science education, the study performed statistical analyses. The findings revealed that VR/AR technology markedly enhanced students’ overall satisfaction and self-efficacy, thereby furnishing empirical evidence for the digital preservation and living inheritance of ICH skills. This research not only offers theoretical underpinnings and practical approaches for the innovative evolution of the Jin-style filigree mosaic art but also serves as a model for the contemporary protection and promotion of other ICH initiatives. Ultimately, the study bolsters the public’s comprehension and appreciation of local culture while propelling the enduring prosperity and development of traditional culture in an age of globalization.

In the era of transition from digitalization to intelligence, Generative Artificial Intelligence (AIGC) acts as a technological force with ontological significance, deeply intervening in the field of living inheritance of Qiaoxiang (hometowns of overseas Chinese) Intangible Cultural Heritage (ICH). While this intervention empowers cultural production and communication, it also triggers profound ethical anxiety: Does the "simulacra" generated by algorithms disintegrate the "authenticity" of ICH? Does the expansion of technological rationality lead to the sinking of the "cultural subjectivity" of inheritors? Based on the cultural ecology of Jiangmen Qiaoxiang, this paper integrates theoretical perspectives from philosophy of technology, media ecology, and cultural sociology to examine the ethical dilemmas of AIGC intervention in ICH inheritance. The study points out that Generative AI has induced a cognitive shift from "historical authenticity" to "digital authenticity," as well as a transfer of power from "endogenous subjects" to "algorithmic agents." Facing ethical risks such as "hallucinatory narratives," "algorithmic bias," and "bodily absence," we must transcend mere techno-optimism and construct an ethical regulation and practical path based on "human-machine collaboration." By establishing the status of inheritors as value legislators, constructing a dual-drive mechanism of "Knowledge Graph + Large Model" in vertical fields, and reshaping the inheritance field of the dialectical unity of "embodiment and disembodiment," we can achieve reconciliation between technological logic and cultural logic, ensuring the living continuation and subjective reshaping of Qiaoxiang ICH in the digital age.

Recently, the General Office of the Ministry of Education issued the Notice on Strengthening Artificial Intelligence Education in Primary and Secondary Schools, which will basically popularize artificial intelligence education in primary and secondary schools before 2030. Nowadays, in the era of artificial intelligence, how to intelligently integrate intangible cultural heritage (ICH) music into primary and secondary school music education, this paper elaborates in detail from building digital curriculum system, exploring intelligent teaching methods, and applying scientific teaching evaluation, and puts forward practical reform paths to better promote the reform and development of primary and secondary school music curriculum teaching in the era of artificial intelligence, and to cultivate students with high aesthetic literacy and innovation ability that meets the needs of the times.

: The article explores the application path of artificial intelligence technology in the inheritance and protection of intangible cultural heritage. Specifically, by constructing digital archives of intangible cultural heritage, we can utilize virtual reality and augmented reality technologies to enrich the interactive experience of intangible cultural heritage; Meanwhile, with the help of big data analysis and user behavior analysis, we can achieve precise dissemination of content related to intangible cultural heritage. Artificial intelligence has also promoted the innovative design and intelligent production of intangible cultural heritage products, broadening the inheritance path of intangible cultural heritage. Taking the Eight Treasures of Yanjing as an example, this paper analyzes the challenges it faces and proposes specific measures for artificial intelligence in data recording, intelligent recognition, innovative design, intelligent dissemination, and protection and repair. Finally, research has shown that the deep integration of artificial intelligence technology provides new impetus for the inheritance and protection of intangible cultural heritage.

This study focuses on the field of artificial intelligence (AI) and explores the application of intelligent systems in the compilation of non-material cultural heritage (NMC) pattern intelligence. Aiming to improve the efficiency and accuracy of drawing data aggregation, the paper has innovated an intelligent architecture based on generative adversarial network (GAN) to achieve automatic and accurate extraction of NMC graphic features. The first step is to tailor the deep learning program for NMC patterns and confirm its feasibility through simulation models. The system is optimized with the help of massive NMC image data, and the fluctuation of algorithm configuration on the collection effect is fully considered. Empirical data show that this intelligent platform has an accuracy of up to 97.5% in the NMC pattern capture operation, and greatly reduces the frequency of human intervention. More strikingly, in the face of the challenge of the diversity of NMC items, the system shows excellent adaptability and is suitable for the collection of a wide range of NMC graphics. Through detailed statistical analysis, the paper confirms the practical value and robust performance of the system.

With the advent of artificial intelligence digitization, intangible cultural heritage faces challenges in preservation and transmission. Utilizing modern technology to achieve digital protection and dissemination has become a crucial issue today. This study enhances the digital inheritance and development of Chinese intangible cultural heritage paper-cutting art through generative AI technologies, specifically Diffusion and LoRA models. The Analytic Hierarchy Process (AHP) was employed to categorize the cultural value of paper-cutting, selecting four core elements: “Spring Festival”, “Chinese Zodiac”, “Women”, and “Birds and Flowers”. Based on these, eight LoRA models were developed to generate paper-cutting-style patterns (using the FLUX.1-dev and Stable Diffusion 1.5 models). In the user satisfaction assessment, the Importance–Performance Analysis (IPA) method was used to analyze four dimensions of the model experience. The results indicate that the LoRA model excels in generating detailed paper-cutting patterns and accurately reproducing cultural elements, particularly in the generation of complex Chinese character designs. User feedback suggests that the LoRA model effectively enhances the digital representation and dissemination of paper-cutting art, though there is room for improvement in terms of generation speed and ease of operation. This study provides a new technological pathway for the digital preservation of intangible cultural heritage and promotes the modernization of paper-cutting art transmission.

The digital image of embroidery has complex edge structure and high repetition rate texture features. Post-processing such as region detection is a challenging task. A long embroidery image data set for learning and training is constructed. Based on the deep network and multi-scale detection structure, the lightweight detection network model GSEm-Net is introduced to detect the long embroidery pattern in real time. Experiments show that compared with yoloV8, the detection accuracy of this method is equivalent, and the detection speed is 1.5 times that of yoloV8, but the generated model is smaller, and it is easier to deploy to low-computing edge devices, which effectively improves the target detection efficiency.

Nowadays, digital information technology has made outstanding achievements in the protection of many large-scale tangible heritage, “digital protection of intangible cultural heritage” is gradually known and used by people, and the data has become a new valuable resource. This paper firstly analyzes the influencing factors of the inheritance of intangible cultural heritage art, and obtains the final fitting results of the logistic regression model. It optimizes the curriculum objectives, curriculum content, and teaching methods of art education, and proposes the reform of art education. Taking Shaanxi folk songs as an example, a survey experiment was designed to analyze the respondents' evaluation of Shaanxi folk songs, and most of the respondents believed that the inheritance and development of folk songs needed to be intervened, and the support rate of "inheritor training" was the highest, with an average score of 5.26, followed by "documentary record" and "nationwide promotion", with a score of 5.24. The students were guided to the teaching practice of non-heritage music inheritance, and their artistic performance and cognition were analyzed through the control test. The mean values of artistic performance and cognitive assessment of the students in the experimental class are 7.984 points and 8.208 points respectively, which are better than those of the control group, indicating that the teaching practice of the experimental class is more efficient and the non-heritage culture can be better inherited and educated.

Artificial Intelligence Generated Content (AIGC) technology combines machine learning and natural language processing to provide a new way to digitally display and disseminate intangible cultural heritage. the technology is based on the fields of deep learning and computer vision to build a theoretical framework that provides practical guidance for the digital transformation of intangible cultural heritage. This study adopts the case study method, taking Wuhan Textile University Jingchu Textile Nonheritage Museum and “Ancient Chinese Loom Virtual Simulation Experiment” as examples, explore the integration of AIGC technology with virtual reality and other technologies to provide an immersive experience, in-depth analysis of the standardization of digitization of non-legacy, the path of resource sharing, as well as the innovative application of design of exhibition space and educational dissemination. The study proposes a progression path for the digital display of NRH through literature review and case studies. the results of the study show that AIGC technology plays an important role in the protection and inheritance of non-legacy, enhances interactivity and immersion, and supports the modern dissemination of traditional culture. At the same time, the study points out the challenges facing the development of AIGC technology, such as data privacy and algorithmic bias, which require further research and policy support to ensure the healthy development of the industry. The deep integration of AIGC technology provides new perspectives and strategies for the sustainable development of non-heritage.

With the gradual integration and development of artificial intelligence and big data technology, AIGC technology is playing an increasingly important role in the field of digital protection and dissemination of intangible cultural heritage in China. By exploring the application status of AIGC technology in the field of intangible cultural heritage, this paper analyzes the challenges faced by China's intangible cultural heritage, and puts forward digital strategies for intangible cultural heritage, in order to promote the digital protection and inheritance of Chinese intangible cultural heritage.

In the context of the digital era, the protection and inheritance of intangible In the context of the digital era, the protection and inheritance of intangible cultural heritage is facing new opportunities and challenges. This paper focuses on the exploration of the digital protection path of intangible cultural heritage-fish lantern dance by using artificial intelligence (AI) technology. This paper summarizes the application status of AI technology in the field of intangible cultural heritage protection, and analyzes the advantages of AI technology in intangible cultural heritage protection. The purpose of this paper is to propose a set of digital cultural heritage protection path of fish lantern dance combined with AI technology, in order to provide new ideas and methods for the inheritance and protection of intangible cultural heritage.

In the era of transition from digital technology to intelligence, Generative Artificial Intelligence (AIGC) is reshaping the existence and communication logic of cultural heritage. As a unique diasporic cultural space in China, Jiangmen Qiaoxiang (hometown of overseas Chinese) faces the decline of its physical field and the rupture of intergenerational memory regarding its Intangible Cultural Heritage (ICH). Traditional digital protection often stops at static "mirror replication," failing to respond to the needs of living inheritance across time, space, and cultures. Drawing on Henri Lefebvre's theory of the production of space and Pierre Bourdieu's field theory, this paper proposes the concept of "Cultural Digital Twin" and explores how Generative AI drives the ontological leap of Qiaoxiang ICH from physical space to digital twin space. The study finds that AIGC produces a digital field of virtual-real symbiosis and dynamic evolution through three mechanisms: "algorithmic reconstruction of representations of space," "embodied simulation of representational spaces," and "interactive co-creation of spatial practice." This process not only achieves the digital proliferation of ICH resources but also triggers the restructuring of power structures and the transformation of capital forms within the Qiaoxiang cultural field. The paper further constructs a digital twin space production model based on "human-machine collaboration" and critically examines issues of technological ethics, algorithmic bias, and digital sovereignty, aiming to provide theoretical interpretation and practical paths for the revival of Qiaoxiang culture in the intelligent age.

In the face of the challenges posed by the globalisation and digitalisation trends, the intergenerational transmission of intangible cultural heritage (ICH) is confronted with issues such as the ageing of heritage bearers and insufficient youth participation. However, the emergence of technologies like generative AI and the Metaverse presents new opportunities for the living transmission of ICH. Currently, the digitisation of ICH faces bottlenecks such as insufficient technical compatibility and the loss of cultural authenticity. This paper uses the theory of innovation diffusion as a framework, focusing on two aspects: technology bridging generational cognition and digital empowerment and cultural authenticity. Through a literature review and case analysis, it systematically explores the mechanisms by which digital technology reshapes the transmission subjects, cultural spaces, and value logic of ICH. The study found that short videos and generative AI enhance young people's participation through scenario-based narratives, but excessive entertainment can easily lead to the symbolic dislocation crisis of intangible cultural heritage techniques and the rupture of cultural identity. Based on the above situation, a 3+2+1 collaborative path is proposed to construct a practical paradigm that balances innovation diffusion and cultural protection, providing theoretical and practical implications for the sustainable intergenerational transmission of intangible cultural heritage.

Intangible Cultural Heritage (ICH) like traditional culinary practices face increasing pressure to adapt to globalization while maintaining their cultural authenticity. Centuries-old traditions in Chinese cuisine are subject to rapid changes for adaptation to contemporary tastes and dietary preferences. The preservation of these cultural practices requires approaches that can enable ICH practitioners to reimagine and recreate ICH for modern contexts. To address this, we created workshops where experienced practitioners of traditional Chinese cuisine co-created recipes using GenAI tools and realized the dishes. We found that GenAI inspired ICH practitioners to innovate recipes based on traditional workflows for broader audiences and adapt to modern dining contexts. However, GenAI-inspired co-creation posed challenges in maintaining the accuracy of original ICH workflows and preserving traditional flavors in the culinary outcomes. This study offers implications for designing human-AI collaborative processes for safeguarding and enhancing culinary ICH.

Safeguarding intangible heritage music increasingly depends on endtoend digital value chains that can faithfully model, generate, track, and remunerate culturally embedded musical knowledge. This paper proposes a generative AI framework that jointly (i) learns a multilayer, ethnomusicologyaware representation across raw audio, symbolic structure, and contextual metadata, (ii) constrains a controllable transformerdiffusion pipeline to preserve modality, microtonal tuning, ornamentation practice, and rhythmic grammar, and (iii) embeds blockchainanchored provenance and smartcontract royalty logic inside the creative pipeline. Using 1,842 recordings (126.3 hours) spanning Southeast Asian gamelan, Chinese Buddhist chant, and Andean panpipe repertoires, we compare our system against an archiveonly baseline and an unconditioned generative baseline. Conditioned generation reduces average modal deviation from canonical tunings from 12.34.1 cents to 4.91.8 cents, decreases rhythmic dynamictimewarping distance by 44.5%, and raises expert authenticity ratings from 3.120.61 to 4.470.28 (ICC(2,k)=0.82). On the valuechain layer, median royalty settlement time drops from 23.7 days to 1.92 days, the Theil inequality index falls from 0.218 to 0.071, and Jains fairness index rises from 0.63 to 0.89. Listenerside evaluation shows higher longtail coverage (+31.4%), improved NDCG@20 (0.3820.497), and a 26% reduction in the hazard of early session abandonment. The findings demonstrate that culturally bounded, rightssensitive generative pipelines can simultaneously enhance preservation fidelity, creative reuse, and equitable community remuneration.

In the context of the deep integration of digital technology iteration and cultural heritage protection, the cross-cultural communication of Intangible Cultural Heritage (ICH) in Qiaoxiang (hometowns of overseas Chinese) is undergoing a paradigm shift from "digital storage" to "intelligent generation." As a significant source of Chinese overseas migration culture, Jiangmen Qiaoxiang's ICH resources carry unique diasporic memories and ethnic identities. However, facing the intergenerational gap of the new generation of overseas Chinese and the contextual barriers of heterogeneous cultures, traditional static display and one-way communication modes have become ineffective. Generative Artificial Intelligence (AIGC), with its powerful multimodal generation, deep semantic understanding, and human-computer interaction capabilities, provides ontological technical support for reconstructing the communication field of Qiaoxiang ICH. Based on theories of media ecology, phenomenology of perception, and narratology, this paper deeply analyzes the triple narrative paradigm shift of Qiaoxiang ICH communication driven by Generative AI: the shift from visual gaze to embodied immersion in "presence" narratives, utilizing multi-sensory channels to reshape the hometown experience of diasporic groups; the shift from static replication to creative generation in "recreation" narratives, activating the endogenous power of ICH through the modern translation of cultural symbols by algorithms; and the shift from one-way inculcation to emotional resonance in "empathy" narratives, rebuilding intergenerational emotional connections through anthropomorphic interaction and affective computing. The study suggests that AIGC is not merely a technical tool but a generative force reconstructing Qiaoxiang cultural memory and identity. By building a "human-machine collaborative" living inheritance mechanism, it can effectively dissolve the "cultural discount" in cross-cultural communication and realize the global expression and localized acceptance of excellent traditional Chinese culture.

Museums often show visions of Cultural Heritage (CH) as tangible forms represented through our current lenses of what they ought to be in our perception, showing reconstructions that show our own limited visions and biases about what we imagine the CH to have been. Often neglected are the human connections to these sites, their childhood memories, their relationships with what happened their, their conceptions of what the CH symbolizes in their lives and their communities. We applied Generative AI (GenAI) to let participants express their visions of CH in concrete forms, showing their relationships to these sites through the process of GenAI interactions that lead to visual depictions full of details revealing their perceptions of the CH. The resulting images are shown as images of different CH locations in Hong Kong on a map as imagined present and future forms, and also as a set of drawings iteratively being sketched by a drawing-robot, which converts the intangible form of record into tangible media. This work demonstrates the use of GenAI technology to empower a form of realization of human imagination for social purpose.

With the development of mid-air interaction, the digital preservation and interactive learning of intangible cultural heritage (ICH) have become increasingly significant. However, the intrinsic significance of the cultural symbols embedded within numerous ICH remains largely obscure to the general public. This paper introduces "Echoes of Antiquity", an interactive installation that utilizes Leap Motion for gesture recognition and generative AI for image processing to vividly illustrate the symbolic elements of Guqin culture, thus bridge the existing chasm in public understanding and appreciation of Guqin’s rich cultural heritage. Specially, our system utilizes Leap Motion to capture gestures and deliver AI-generated images as feedback, thereby enhancing the understanding and retention of the Guqin’s cultural heritage through the seamless integration of motion and visual cues.

Traditional ceramic patterns are an essential component of intangible cultural heritage, embodying aesthetics, region, and cultural identity. However, due to age, insufficient documentation, and the decline of traditional craftsmanship, many of these visual resources are at risk of decline and loss. To address this challenge, this study proposes an AI-based generative framework for the digital preservation and reconstruction of ceramic heritage patterns. This study constructs a dataset of over 2,000 high-resolution ceramic pattern images from museum archives and academic resources, covering representative categories such as blue-and-white porcelain, celadon, and underglaze red. The proposed method utilizes a modified CycleGAN architecture enhanced with an attention mechanism and cultural consistency constraints to capture structural patterns and stylistic authenticity. Experimental results demonstrate superior performance compared to baseline models, improving the Fréchet Inception Distance (FID), Structural Similarity Index (SSIM), and Cultural Consistency Score (CCS). User evaluations involving ceramic experts and design professionals further validate the model's ability to generate visually faithful and culturally authentic patterns. This research highlights the potential of generative AI in preserving intangible cultural heritage while promoting creative innovation in digital ceramic design.

This study explores how artificial intelligence (AI) is being used to support the sustainable transmission of intangible cultural heritage (ICH). While much of the existing research focuses either on technical innovation or cultural theory, this paper brings the two together through a dual-framework approach that considers both how AI systems work and what cultural roles they serve. Drawing on nine recent cases from Chinaincluding projects in embroidery, paper-cutting, and operathe study traces how analytical models contribute to documentation and interpretation, while generative techniques help recreate traditional patterns in new formats. It also looks at how immersive interfaces and recommendation algorithms shape user experience, and raises concerns about authenticity, equity, and creative diversity. The findings suggest that AIs role in heritage should move beyond digitization to include creative co-production, participatory design, and inclusive governance. This research offers a structured foundation for future interdisciplinary work at the intersection of AI and culture, and provides practical insights for developers, cultural institutions, and policymakers seeking to align technological innovation with the values and needs of living heritage.

As an intangible cultural heritage of China, Cloisonne embodies rich historical and cultural significance alongside unique artistic value. However, rapid modernization has led to a growing disconnection in traditional crafts, posing challenges for both preservation and innovation. This study explores innovative visual image generation methods using generative AI technologies—specifically Stable Diffusion and Midjourney—to design and create cultural product images inspired by Cloisonne. Employing literature review, design practice and expert evaluation, the research covers generative AI tools, concepts of intangible cultural heritage and cultural goods, and new approaches to digitalization and design practice. Experimentally, a Cloisonne knowledge graph was constructed as a theoretical basis, followed by building and training a LoRA model. Stable Diffusion was then used to generate visual images of Cloisonne cultural products, which were further refined with Midjourney. Results demonstrate that these AI tools effectively produce creative and artistic cultural product visuals, revitalizing Cloisonne with fresh vitality and innovation, while advancing the digital preservation and modernization of intangible cultural heritage.

Objective, This study uses Yuxian paper-cutting as a case study to analyze fundamental limitations in mainstream generative models and investigates generative design methods capable of accurately reproducing the Yuxian paper-cutting style. Method, The paper examines the technical process and developmental trends of Yuxian paper-cutting, analyzes policy support for generative AI in paper-cutting design, and discusses the constraints of mainstream generative models in data training. To address their inadequacy in replicating the Yuxian style, this research reconstructs a high-quality dataset of paper-cutting images, trains a specialized generative model, and employs visual evaluation methods to validate its effectiveness and feasibility. Conclusion, This study proposes an AI-based generative design method for Yuxian paper-cutting. It surpasses both traditional methods and mainstream generative models in design efficiency and artistic expression while demonstrating high reusability. The method effectively reproduces the visual style and technical characteristics of Yuxian paper-cutting, fosters the integration of cultural innovation and technology, and provides a novel pathway for the revitalization and innovation of intangible cultural heritage.

With the development of digital technologies, the limitations of static records in digital preservation of Intangible Cultural Heritage (ICH) in conveying deep cultural connotations have become apparent. Intelligent technologies (VR/AI/MR) provide a new pathway for the living interpretation of ICH. This study proposes an intelligent technology-based “Immersive-Cognitive-Identificatory Conduction Model” to reveal the generative mechanism of cultural perception depth. From the immersion to the cognition stage, spatiotemporal reconstruction and cognitive reinforcement are achieved through dynamic modeling, semantic activation, and multimodal interaction. From the cognition to the identification stage, embodied cognition, ritual translation, and affective computing are leveraged to internalize practical memory and drive empathy. The research outcome is an intelligent technical implementation pathway based on the Immersive-Cognitive-Identificatory Conduction Model. It employs technical means such as dynamic contextual modeling, semantic activation empowered by large models, and multimodal interaction to open the channel from “immersion” to “cognition”. Furthermore, it explores how to utilize mechanisms like embodied cognition, ritual translation, and empathy modeling to achieve the sublimation from “cognition” to “identification”. This work is not only a technical systematization of existing ICH-VR practices, but also provides new ideas for the future direction of constructing deep cultural experience systems.

Aiming at the problem of insufficient precision in the digital media communication of Foshan intangible cultural heritage, this study designed the "Intangible Cultural Heritage - Audience Interest Association Recommendation Algorithm (NH-AIR)" and explored the communication strategy integrating AI technology. The experiment used 2,300 texts, 1,500 images, 800 audio data of 8 types of intangible cultural heritage projects in Foshan, and 28,600 behavior records of 1,200 audiences. The simulation results show that the accuracy of the NH-AIR algorithm is 86.7%, which is 21.3% higher than the traditional collaborative filtering; the recall rate is 83.5%, which is 18.9% better than the content-based recommendation; the MAP value is 0.84, which is 23.7% higher than the Wide&Deep model. In the segmented scenarios, the accuracy of Cantonese opera recommendation is 91.2%, the recall rate of endangered skills is increased by 24.5%, the average daily stay time of users increases by 27 minutes, and the sharing rate increases by 42%. The "technology-content-channel" strategy system constructed by the study provides an effective path for the digital communication of Foshan intangible cultural heritage, and proves that AI technology can improve the reach efficiency by more than 40%.

In this paper, we propose a low-code, AI-assisted workflow for the digital revitalization of intangible cultural heritage (ICH), focusing on the Shuizu Dance in Conghua, China. Leveraging generative models—ChatGPT for textual prompt construction, Doubao for image synthesis, and Kling for motion video generation—we design and implement a modular pipeline that enables non-technical users to generate culturally grounded visual narratives. A multi-dimensional evaluation framework comprising eight criteria (e.g., motion fidelity, costume accuracy, communicative clarity) was applied to assess output quality using a structured audience study (n=15). Results show that while current generative models provide high visual appeal and pedagogical value, they fall short in replicating nuanced choreography and attire without domain-specific data. This work contributes a reproducible methodology for low-resource cultural digitization, and outlines future enhancements through motion capture, ontology-based prompt refinement, and human-in-the-loop feedback mechanisms.

Filigree art, which represents typical intricate metalwork, has been captivating audiences worldwide with its delicate lace-like patterns and interwoven metal wires’ refined aesthetics. Particularly, Chinese Intangible Cultural Heritage filigree craftsmanship has a unique aesthetic value in fine patterns and complex three-dimensional shapes. However, designing and creating filigree artworks is a labor-intensive and technically complex task and often requires extensive training and a deep understanding of the craft, which limits its design aesthetic and cultural continuity. Aiming to overcome these challenges, this study proposes an artificial intelligence (AI) -aided method that uses AI-generated content (AIGC) technology to accelerate the visualization process of this time-consuming and intricate craft by investigating the role of AI in craft design. First, a comprehensive study of filigree art culture is conducted to identify more than ten historic filigree techniques to obtain AI opportunities. Then, an AI-powered framework called AIFiligree is developed by optimizing culture-based labels and training parameters, enabling the generation of highly authentic fine filigree structures. Further, user workflows are introduced to support diverse design scenarios. Through user studies involving 22 filigree experts and 16 designers, we finally gained insights into AI’s opportunities and challenges in cultural learning, expression, and design.

Guizhou batik is a typical representative of textile dyeing intangible cultural heritage. This paper explores the feasibility of integrating generative AI with Guizhou batik by examining the current state of both fields. It proposes how generative AI can address existing challenges in Guizhou batik, such as the uneven distribution of inheritors and the outdated pattern symbols and design language. Furthermore, it discusses how traditional handicrafts can coexist with digital intelligence in the modern era. The study also demonstrates that the introduction of generative AI not only enables efficient design and enhances artistic expression but also preserves the traditional characteristics of batik craftsmanship, providing insights into the digital-intelligent integration of Guizhou batik art.

Lacquerware, a representative craft of Chinese intangible cultural heritage, is renowned for its layered aesthetics and durability but faces declining engagement. While prior human-computer interaction research has explored embedding interactive circuits to transform lacquerware into responsive artifacts, most studies have focused on fabrication techniques rather than supporting makers in creatively designing such interactions at a low threshold. To address this gap, we present LacAIDes, a Generative AI powered creativity-support tool built on a multi-agent workflow aligned with the double diamond model of design thinking. LacAIDes enables exploration and creation of culturally grounded interactive circuits without requiring prior technical expertise. We evaluated LacAIDes in a longitudinal workshop with 34 participants using a mixed-method approach. Results show that LacAIDes demonstrated high usability, enhanced creative engagement in craft making, and encouraged critical reflection on the role of Generative AI in digital craft practices. This work contributes to human-computer interaction by introducing a novel creativity-support tool and providing empirical insights into revitalizing traditional craft making through Generative AI.

Addressing issues such as the discontinuity of intangible cultural heritage (ICH) New Year painting techniques, the static nature of digital conversion, and stylistic semantic gaps and misinterpretations of cultural symbols in generative AI's integration with traditional art, this study proposes and constructs a generative AI digital illustration collaborative creation system that integrates ICH New Year painting techniques. First, by analyzing core techniques of Yangjiabu and Taohuawu school New Year paintings, we establish an encoding framework based on diffusion models. This framework utilizes parameters such as color-layer coefficients, line engraving roughness, and composition white space ratio to convert traditional techniques into computable parameters. Subsequently, we achieve precise mapping between “text instructions, technique parameters, and image generation.” Finally, a three-tier system architecture—data layer, algorithm layer, application layer—was established to form a closed-loop collaborative workflow. This enriches interdisciplinary research outcomes in digital humanities and artistic AI, driving innovative transformation and sustainable dissemination of traditional visual arts in the digital era [9].

With the rapid development of artificial intelligence, particularly AI-Generated Content (AIGC) technologies, the digital innovation of intangible cultural heritage has entered a new stage of opportunity. Zigong lantern art, as a representative form of traditional Chinese lantern craftsmanship, now faces an urgent need for transformation in terms of design methods, dissemination channels, and modes of artistic expression. This study takes AIGC as a starting point to explore its application pathways and innovative potential in the design of Zigong lanterns. The paper first reviews the traditional craftsmanship and cultural characteristics of Zigong lanterns, and, in conjunction with current developments in AIGC and image generation mechanisms, proposes a collaborative design model of "AI generation - human selection - craft transformation." In the design practice, the theme “Camel Shadows Along the Silk Road” is used to generate visual design concepts via Midjourney and Stable Diffusion, and the transition from AI-generated images to physical lantern installations is tested. Findings indicate that AIGC can effectively enhance design efficiency and the quality of creative output, offering significant advantages in visual ideation, form expression, and thematic exploration. However, challenges such as cultural misrepresentation and distorted image details persist. The paper concludes by offering strategic recommendations for the application of AIGC in lantern art, aiming to provide a reference for the integrated development of traditional crafts and intelligent design.

The rise of generative artificial intelligence technology provides a new path for the design innovation and market expansion of non-heritage cultural and creative products. This paper takes AI-enabled non-heritage cultural and creative products as the research object, and systematically explores its market development characteristics and economic benefit enhancement mechanism. Based on generative adversarial network and residual network, the intelligent optimization framework of non-heritage cultural and creative product design is constructed. Through user demand research, perceptual imagery analysis and controlled experiments, the effectiveness of AI technology in improving design efficiency and product quality is verified. Combining the algorithm test and economic benefit assessment of four types of cultural and creative products, namely hand puppet, earrings, fan and book, to reveal the driving effect of AI-enabled on the market competitiveness and economic returns of non-heritage cultural and creative products. After adopting AI-assisted, the economic benefits of each product are significantly improved, and the economic benefits of the hand puppet and earrings show a growing trend, in which the final benefit of the hand puppet reaches 1,312 yuan/d, and that of the earrings reaches 1,118 yuan/d. Adopting AI-assisted styling design of the cultural and creative products is feasible, which not only improves the design effect of the cultural and creative products but also enhances the economic benefits by doing so.

This study explores the design of Metaverse technologies for preserving and teaching Lanna Dance, a traditional cultural heritage of Northern Thailand. It addresses the challenges of sustaining intangible cultural heritage by developing an immersive learning system that integrates motion capture, generative AI, and gamified virtual environments. Grounded in Situated Learning Theory and adaptive learning, the platform features four interactive zones, the Motion Showcase, Knowledge Exhibition, Video and AI Interaction, and Interactive Game Zone, offering learners multifaceted, context-rich experiences. Using a quasi-experimental design with 36 participants, the study evaluates learning outcomes, motivation, and user satisfaction. Results show significant improvements in knowledge acquisition and intrinsic motivation, along with high usability scores, indicating the effectiveness of immersive digital environments in enhancing cultural appreciation and skill development. The findings offer practical insights into Metaverse design for immersive cultural education, supporting educators, cultural institutions, and policymakers in developing scalable and engaging solutions for preserving intangible heritage through emerging technologies.

In the intertwined process of globalization and digitalization, folk intangible cultural heritage is undergoing a transformation—from the decline of traditional transmission methods to the innovation and reform of dissemination approaches. The recently emerged generative AI (AIGC) offers new pathways for the protection and inheritance of intangible cultural heritage. This paper takes two major festival-based intangible cultural heritages—the Chinese Dragon Boat Festival and the Spanish Fallas Festival—as examples. From a cross-cultural comparative perspective, it applies ecological cultural theory and embeddedness theory to explain the technological applications and institutional adaptations of AIGC in different cultural contexts. Based on empirical evidence, it constructs a three-dimensional analytical framework of “technological application-institutional structure-cultural expression,” examining the similarities and differences between the two countries’ mechanisms in terms of protection entities, technological means, and cultural transmission. It is found that China’s protection mechanism features government leadership and social participation, with AIGC empowering digital archiving, immersive education, and cultural-creative content production. In contrast, the Fallas Festival relies on community participation and artistic associations, with AIGC supporting grassroots autonomy and Fallas-specific creativity. The Dragon Boat Festival is rooted in Confucian cultural contexts, focusing on themes like disease prevention and patriotic narratives. Meanwhile, the Fallas Festival reflects a shared Spanish value of creativity, satire, and collective celebration. In both cases, AIGC is used to engage younger generations and expand public participation, highlighting both differences and overlaps in cross-cultural dissemination. This paper argues that AIGC is guiding folk intangible cultural heritage from a state of “static memory” to one of “intelligent expression.” In the next phase, leveraging shared digital resources, ICH metaverse systems, and algorithmic governance mechanisms can help construct a global, collaborative digital heritage ecosystem, thus enabling the sustainable cultural creation of intangible heritage.

In order to solve the problems of lack of immersion and interactivity in the current digital communication of intangible cultural heritage (intangible cultural heritage), and the difficulty of stimulating users' cultural cognition and emotional resonance, this paper introduces the theory of embodied cognition as a design guide and proposes a user-centered interaction framework with practical application in digital heritage dissemination.By constructing a digital interaction model of the three elements of "perception-operation-situation", based on typical intangible cultural heritage elements in Shaanxi, a WeChat Mini Program is developed for young users, integrating visual stimulation, interactive participation, and cultural context to enhance engagement. In the questionnaire survey and user test, the proposed interaction model is verified. The results show that embodied interaction design can significantly enhance users' interest, participation and cultural understanding of intangible cultural heritage content, and provide a new design path and practical basis for the digital communication of intangible cultural heritage.

Incorporation of AI into the developmental process of illustrations of ICH is not only a great advancement in the process of utilizing technology to put into practice ICH, but also shows a shift from the static use of traditional cultural factors in the representations of the ICH. In this research context, references shall be made to how information science and AI, particularly in connection with computer technologies, can be used for better visualization and sharing of intangible cultural heritage with generations to come. This paper discusses how the AI computational methods, especially the deep learning and generative models can mine and replicate the historical and cultural data to generate new, relevant, but culturally authentic illustrations of the heritage. This research will also establish how AI tools can recreate and reimagine traditional signifiers belonging to intangible cultural heritage by using image recognitions, natural language processing, and generative adversarial networks (GANs). Unlike traditional arts that have to be copied to conform to the current standards, these technologies not only replicate, but they also bring in new approaches by providing novel interpretations to traditional arts while at the same time conserving their originality as discussed below. This is important because it is only now that due to the advancement of AI, culturally relevant illustrations are created, which can be shared through digital platforms making heritage more accessible. The results will help to determine whether AI can be used as an instrument that can be effective in the sphere of conservation, as well as open up a possibility for further creation in the sphere of cultural heritage. This research will also provide a reference point for artists, historians and cultural organizations, who want to use AI in conserving and repurposing traditional or cultural asset in the modern socio-technological context.

This article proposes a multimodal generative AI model for digital reconstruction of intangible cultural heritage, constructing a generative network structure for three sub tasks: image, action, and language. The model integrates structures such as CycleGAN, Diffusion, PoseGAN, and VITS to handle tasks such as pattern style transfer, dynamic behavior reconstruction, and semantic speech generation. In the modeling process, a composite objective function system was designed, including adversarial loss, cyclic consistency loss, temporal action smoothing term, and semantic similarity loss, to improve the fidelity and cultural consistency of the generated output. The system module consists of five stages: multimodal data acquisition, semantic label embedding, cross modal training, generative control, and user interaction. In typical intangible cultural heritage tasks such as Su embroidery, Huizhou opera, and Miao mythology, the model significantly outperforms traditional methods in SSIM, FID, KFM, BLEU, MOS, and other indicators, verifying its stability and adaptability under small sample and non paired data conditions. This method can provide technical support for intelligent expression, visual dissemination, and human-machine collaborative re creation of intangible cultural heritage

This paper studies the application possibilities of AI technology in promoting the integrated development of intangible cultural heritage and rural creativity, and focuses on the practicality of convolutional neural networks (CNN), generative adversarial networks (GAN), and Transformer in image recognition, generation, and text processing. By constructing a multimodal framework that integrates images, texts and sounds, an extensible solution suitable for multiple scenarios has been formed. In the Suzhou embroidery image recognition experiment, the accuracy rate of CNN is 91.4%. In the diffusion simulation process for Miao embroidery patterns, more than 2,000 samples were generated, among which 67% of the generated samples were actually applied. The click-through rate of the experimental platform using the recommendation system increased by 70.5%, and the conversion rate rose to 18.9%. It can be seen from this that AI can not only significantly facilitate the digital presentation of intangible cultural heritage information and effectively enhance the effect of dissemination and conversion, but also play a significant role in the construction of cultural and rural creative ecosystems, providing theoretical support and operational guidance for the establishment of an intelligent mechanism for the intangible cultural heritage industry.

Advancements in computer technology, particularly Generative Pre-trained Transformers (GPT) and holographic rendering, have enabled the development of innovative interactive systems with broad applications in smart cities and cultural heritage preservation. This study proposes a framework integrating GPT with multimodal fusion and real-time holographic rendering to construct virtual characters capable of delivering dynamic narratives. A fine-tuned GPT model, trained on a dataset of over 1.2 million tokens, ensures linguistic accuracy and contextual fidelity, while the multimodal pipeline synchronizes text, audio, and visual elements to create lifelike holographic avatars. Experimental results demonstrate the system’s effectiveness, achieving a BLEU score of 92.4% for narrative accuracy and an average frame latency of 24 milliseconds, meeting the requirements for real-time interaction. Key innovations include the seamless integration of AI-driven semantic generation with immersive visualization techniques, providing a scalable, adaptive solution for interactive storytelling. Moreover, the holographic rendering system, leveraging advanced optical simulation techniques such as Bidirectional Reflectance Distribution Functions (BRDF), enables the realistic visualization of objects and environments, making it highly suitable for applications in urban digital twins and immersive public spaces within smart cities. This research highlights the transformative potential of computational technologies in enhancing audience engagement, promoting cultural preservation, and advancing smart city infrastructures. By bridging the gap between language processing and holographic rendering, this study establishes a foundation for next-generation virtual experiences, showcasing the potential of combining AI and optical visualization to redefine interactive systems for diverse applications.

Nanjing Yunjin, a UNESCO-recognized intangible cultural heritage, represents a pinnacle of Chinese brocade weaving with its intricate patterns, symbolic meanings, and historical significance. Modern challenges like loss of traditional tech- niques and declining demand threaten its preservation. This paper introduces KGGAN-Yunjin, an AI-driven framework fusing knowledge graphs (KGs) with generative adversarial networks (GANs) for cultural gene inheritance and generative design. The Yunjin Cultural Gene Knowledge Graph (YCG-KG) encodes patterns, materials, symbols, and constraints, guiding the GAN for authentic yet innovative designs. A human-AI feedback loop refines outputs for adaptability. This novel integration embeds cultural knowledge into generation, enforcing fidelity, diversity, and feasibility, while addressing gaps in methods by incorporating weaving-specific rules and iterative refinement. Experiments on 1,500 Yunjin patterns show superior performance over baselines in FID, recall, expert scores, and conformity rate. Ablation studies confirm key components. User studies highlight accelerated workflows and reduced modifications. KGGAN-Yunjin provides a sustainable model for heritage revitalization via AI, bridging tradition and modernity while preserving Yunjin's legacy.

Yanchuan cloth patch painting, a Shaanxi intangible cultural heritage, serves as a significant material carrier for the inheritance of Yellow River culture. However, its inheritance faces the risk of generational gaps and innovation dilemmas due to the experience-dependent creation model. This study focuses on the application of generative artificial intelligence technology in the inheritance of intangible cultural heritage, proposing a diffusion model fine-tuning method for constructing a professional dataset. This method includes collecting 1380 samples of Yanchuan cloth patch paintings, electronically preprocessing them, and constructing the Yanchuan Cloth Patch Painting Dataset (CYCPP) through manual annotation. The CYCPP dataset is used to fine-tune the diffusion model. Image generation experiments are conducted using the fine-tuned diffusion model. The CYCPP model is solidified after mixed evaluation, and the CYCPP model is used for image generation of Yanchuan cloth patch paintings. Experiments show that the generative design method optimizes the hand-painting process, and the new method can support the creation of Yanchuan cloth patch paintings. This study provides an effective technical method for breaking the predicament of "loss of skills due to the death of people" in intangible cultural heritage.

Exploring generative artificial intelligence and Liangping New Year painting cultural and creative design strategies, expanding the application scope of artificial intelligence technology, and promoting the modern expression and innovative development of intangible cultural heritage. The research is based on the discipline of design studies, integrating theories from computer science, semiotics, and other disciplines to analyze the symbolic connotations and characteristics of Liangping New Year paintings. It employs machine learning algorithms based on diffusion models, combined with LoRA model fine-tuning techniques, to achieve precise extraction and innovative generation of Liangping New Year painting styles. Applying generative AI to intangible cultural heritage cultural and creative design not only enriches the forms of expression for intangible cultural heritage but also provides directional references for its modern transformation and technological applications.

The preservation of cultural heritage (CH) is a complex and promising field. Driven by technological advancements, digitization has emerged as a crucial approach for revitalizing tangible/intangible cultural heritage (TCH/ICH). However, current research and practice remain limited in their exploration of abstract forms of ICH, such as traditional philosophies and ideologies. In this study, utilizing Zen as a context, we designed an immersive mixed reality (MR) experience system, Flowing with Zen, based on formative study and cultural symbol analysis. The MR system integrates multi-modal interfaces, motion capture, environmental sensing, and generative computing, enabling users to engage with four scenarios through meditation, life appreciation, and experiential Zen practice, providing the embodied experience of Zen. Comparative user evaluation (N = 51) revealed that the MR system has significant advantages in eliciting engagement and interest from users, enhancing their aesthetic appreciation and cultural understanding, and increasing the accessibility of Zen. Our research proposes a novel approach and design inspiration for the digital inheritance of abstract ICH.

This research explores the computational empowerment of intangible cultural heritage through interactive generative platforms. Prototypes in TouchDesigner software visualize traditional Kam minority patterns by applying particle system effects to highlight symbolic meanings. Users actively transform heritage visuals through real-time interaction, fostering cultural appreciation. Technical realization involves visual programming to construct specialized generative workflows. Phases of diffusion and dissipation of culturally significant motifs are configured procedurally. Preliminary explorations will inform training generative AI models by discerning cultural logic. The goal is an adaptive living database where tradition evolves algorithmically. This pioneering approach synergizes heritage and technology to maintain intangible culture. It provides a model for participatory digital curation where communities actively shape legacies. Limitations around complexity persist. However, the research pioneers cultural resilience through computational creativity.

Cultural Heritage is not just about tangible artifacts; it also includes intangible elements such as personal memories, community ties, and envisioned futures. Traditional museums and archives often emphasize physical items like architectural pieces and photos, while overlooking people’s personal and emotional connections to cultural heritage. To illustrate the personal connections people have with cultural heritage sites, we designed an exhibition that displayed images created by participants, which represent their perspectives and future visions of cultural heritage sites. The exhibition’s images, generated through GenAI, helped participants narratively describe cultural heritage locations, allowing them to express their visions of future threats like over-tourism and climate change on these sites. Contrary to constraints, co-creating with Generative AI associates participants with personal memories of cultural heritage, stimulating personal narratives and promoting deep reflection on cultural heritage preservation. The dissemination strategies we designed illustrate the use of GenAI to empower the expression of matters of cultural value beyond the physical.

Performance artforms like Peking opera face transmission challenges due to the extensive passive listening required to understand their nuance. To create engaging forms of experiencing auditory Intangible Cultural Heritage (ICH), we designed a spatial interaction-based segmented-audio (SISA) Virtual Reality system that transforms passive ICH experiences into active ones. We undertook: (1) a co-design workshop with seven stakeholders to establish design requirements, (2) prototyping with five participants to validate design elements, and (3) user testing with 16 participants exploring Peking Opera. We designed transformations of temporal music into spatial interactions by cutting sounds into short audio segments, applying t-SNE algorithm to cluster audio segments spatially. Users navigate through these sounds by their similarity in audio property. Analysis revealed two distinct interaction patterns (Progressive and Adaptive), and demonstrated SISA’s efficacy in facilitating active auditory ICH engagement. Our work illuminates the design process for enriching traditional performance artform using spatially-tuned forms of listening.

As part of the Intangible Cultural Heritage, Bridging the Past, Present and Future (INT-ACT) project, we investigate how Extended Reality (XR) technologies can meaningfully engage users with cultural content by monitoring their physiological and affective responses. While immersive XR systems offer new ways of exploring heritage, their impact on users’ internal states remains underexplored. In this study, we present a multimodal experimental setup using EmotiBit, a wearable biosensing platform, to monitor real-time physiological signals during cultural XR interaction. Participants were evaluated across three activities representing varying cognitive and sensory loads: immersive interaction with the INT-ACT XR Demonstrator, composing work emails (a low-stimulation control task), and passive movie watching. Our aim is to quantify how cultural XR experiences influence biosignals such as electrodermal activity and heart rate. The findings reveal distinct physiological patterns across conditions, suggesting that biosignal monitoring can inform the design of adaptive XR environments that are responsive to user states. This work contributes to INT-ACT’s broader objective of creating intelligent, inclusive, and emotionally resonant cultural heritage experiences.

This study presents Little Hero Wins the Masks, a multiplayer VR experience combining an interactive game table and a multiplayer VR environment. The game synchronized objects and events between the two platforms in real time, allowing players to collaboratively create immersive experiences. Through the user study, we analyzed the player interaction and experience in VR games with social elements. The goal is to offer insights for future VR development and explore ways to enhance the sociability of VR games. By integrating these interactive elements, the research aims to contribute to the development of more engaging and socially immersive VR games. The findings provide practical guidance for developers seeking to design VR systems that foster real-time, shared interactions among players while addressing technical challenges in cross-platform synchronization.

With the development of digital technology, intangible cultural heritage (ICH) enthusiasts have an increasingly high demand for the learning experience of intangible cultural heritage. The appearance of intangible cultural heritage experience courses meets the demand of intangible cultural heritage enthusiasts for experiential learning to a certain extent, which plays a positive role in promoting the protection and inheritance of intangible cultural heritage. However, there is no systematic research and design specification on how to convey the intangible cultural heritage knowledge and value in experiential courses, which leads to learners' emphasis on the experiential process and lack of cognition of the content of intangible cultural heritage itself. In this research, learners will build personalized knowledge system for intangible cultural heritage based on embodied interaction. Immersive virtual reality will be applied in the classroom as a teaching tool to enable learners to do embodied creation practice. Through practice and qualitative analysis, it has been proved that this method deepens learners' cognition of intangible cultural heritage and learners can complete high-quality artworks.

No abstract available

In order to make the non-heritage culture of Yicheng Flower Drum more relevant to the trend of the digital era and promote its dissemination and inheritance, the design and application of gesture recognition and virtual reality technologies guided by embodied cognition theory in the process of non-heritage culture dissemination is studied. At the same time, it will enhance the interaction between people and NRM culture, stimulate the audience’s interest in understanding NRM and spreading NRM, and create awareness of preserving NRM culture. Using embodied cognition as a theoretical guide, expanding the unidirectional communication mode through human-computer interaction close to natural behavior and cooperating with multisensory information reception channels, so as to construct an embodied and immersive interactive atmosphere for the participants and enable them to naturally form the cognition and understanding of the traditional culture in the process of interaction. The dissemination of the non-heritage culture Yicheng Flower Drum can take the theory of embodied cognition as an entry point, and through the virtual and real scenes of Yicheng Flower Drum and the immersive experience, we can empower the interaction design of non-heritage culture dissemination of the virtual and real, and provide a new method for the research of digital design of non-heritage culture.

Intangible cultural heritage preservation has been made progressively difficult owing to scattered documentation, loss of indigenous knowledge, and restricted accessibility for younger generations. Current solutions lean towards static digital collections or low-fidelity 3D reconstructions, which do not accurately record contextual interactions and immediate immersive exposures. Conventional solutions like rudimentary multimedia repositories and conventional VR visualization models do not have semantic connectivity, adaptive knowledge migration, and intelligent understanding of cultural context. To solve these problems, a Hybrid Graph Convolutional Network with Transformer-based Attention (HGCT-A) is designed, combining VR technology with graph-based relational learning and multi-head attention to promote cultural knowledge connection, interaction realism, and immersive learning. Experimental testing proves that the HGCT-A model has 97.8% accuracy and 96.4 % F1-score, outperforming traditional models. The comparative evaluation reiterates the superiority of HGCT-A in semantic preservation, dynamic adaptation, and user involvement.

The preservation and exhibition of intangible cultural heritage (ICH) through traditional methods are often faced with the challenges of low interactivity, dispersed documentation, and static exhibitions that do not capture the immersive and experiential qualitative of cultural practices. These limitations hinder audience interaction and constrain the potential of such systems to transmit the dynamic and evolving nature of ICH. As a countermeasure to these hurdles, this research offers a Virtual Reality (VR) technology-based digital protection platform for ICH. VR presents an innovative solution by building interactive, three-dimensional environments where the people engage with cultural expressions like rituals, performances, crafts, and oral traditions in real time. The proposed system combines digital archiving, interactive narrative, and simulation mechanisms to bring increased accessibility and increased understanding of ICH. Comparative analysis with other traditional documentation processes and earlier digital methods shows that the VR-based platform enhances immersion, engagement, and retention of cultural knowledge significantly. Empirical findings depict greater satisfaction and understanding among users who go through VR-driven cultural simulations than in traditional methods. Though technical hurdles continue in content development and system tuning, the conclusions confirm the value of VR in preserving ICH and establish a forward-thinking framework for future digital preservation and learning uses.

This study proposes a multi-sensory Augmented Reality (AR) system integrated with custom flexible electronic skin technology, focusing on addressing the lack of haptic feedback in the digital inheritance of the Hong Kong Yulan Festival (Hungry Ghosts Festival) intangible cultural heritage (ICH). The goal is to enhance the authenticity of user experience and cultural perception when interacting with virtual cultural relics of the Yulan Festival. By integrating AR's scene reconstruction capabilities with customizable haptic feedback technology, the system simulates the vibration physical properties and material pressure sensations of characteristic cultural relics of the Yulan Festival, compensating for the deficiency of physical interaction experience in the digital communication of ICH by traditional AR technologies. The flexible electronic skin adopts a modular design, featuring excellent wearing adaptability and environmental compatibility. Combined with the audio-visual immersion brought by AR technology, it constructs an efficient augmented reality interaction framework for technology-empowered traditional culture. Comparative experiments were conducted using the interaction with virtual cultural relics of the Hong Kong Yulan Festival as a standardized scenario, verifying the key role of haptic feedback in improving users' spatial presence, sense of participation, and cultural authenticity. This research provides an extensible technical solution for the digital inheritance of ICH, which can be widely applied to ICH interactive exhibition scenarios requiring enhanced haptic experience.

Traditional Chinese opera costumes are vital carriers of intangible cultural heritage, embodying intricate craftsmanship, symbolic aesthetics, and cultural narratives. However, conventional pedagogy struggles to convey their complexity and cultural depth due to limitations in static, lecture-based teaching methods. This study proposes an immersive Virtual Reality (VR)-based teaching model that integrates high-fidelity 3D modeling, semantic annotation, and real-time rendering optimization—specifically Level of Detail (LOD) and Occlusion Culling (OC)—to enhance the design education and cultural transmission of traditional Chinese opera costumes. A controlled experiment involving 80 undergraduate students was conducted to compare the VR-based model with traditional teaching methods across five dimensions: learning effectiveness, user experience, cultural understanding, technological adaptability, and instructional interaction. Results demonstrated that the VR-based approach significantly improved educational outcomes, particularly in interactive engagement and practical performance, while maintaining high rendering efficiency and visual fidelity. This work contributes a technically optimized, pedagogically grounded framework for integrating immersive technology into cultural heritage education, offering a scalable solution for revitalizing intangible traditions in the digital era.

The preservation of intangible cultural heritage (ICH) faces increasing challenges due to globalization, generational gaps, and loss of traditional knowledge carriers. To address this, research propose the design and application of a digital protection platform for intangible cultural heritage utilizing Virtual Reality (VR) technology, aimed at immersive learning, cultural preservation, and public engagement. The platform leverages 3D scanning, motion capture, and VR interaction frameworks to digitize traditional crafts, folklore, rituals, music, and dance in high fidelity. A modular system was developed using the Unity3D engine, integrating a knowledge database, real-time rendering modules, and interactive VR scenarios for both web and head-mounted displays. A dataset of over 300 cultural elements was collected from regional archives and field recordings, with contributions from heritage practitioners. Usability studies with over 120 participants showed that the platform achieved a cultural immersion satisfaction rate of 98.7%, with a learning retention improvement of 38% compared to conventional video documentation. The VR interface enabled virtual apprenticeship experiences, allowing users to interact with tools, materials, and masters in a simulated environment.

Intangible cultural heritage (ICH) performing arts, particularly their auditory elements, face significant challenges in transmission and engagement among younger generations due to their inherently temporal and passive nature of appreciation. To address this challenge, we present a Spatial Interaction-based Segmented-Audio (SISA) system in Virtual Reality (VR) that transforms temporal auditory experiences into interactive spatial explorations. Our approach segments audio content and applies t-SNE algorithm for spatial clustering within VR environments. In this paper, we demonstrate SISA implementation through four VR scenes featuring two ICH genres - Peking Opera and Meshrep - each incorporating 5-second and 10-second audio segments. Through user testing with 16 participants, we explored users’ perceptions and interactions with SISA system within these VR environments. Our work advances technology-mediated cultural preservation by establishing a system and framework for converting temporal performances into navigable spatial experiences, creating new pathways for ICH engagement.

This research, developed in collaboration with inheritors of intangible cultural heritage (ICH) bamboo weaving, digitally translates traditional Chinese bamboo weaving techniques into a virtual reality (VR) gesture recognition interaction system. In this system, the user’s hands act as proxies for bamboo strips, enabling the weaving process through coordinated hand gestures. The system allows users to clearly understand the structural principles of bamboo weaving while offering a novel and engaging gestural interaction experience. It also opens new possibilities for integrating bamboo weaving into the domain of virtual reality art, contributing to the broader dissemination and preservation of this traditional craft.

This paper first proposes a virtual simulation platform for heritage protection. A design method for non-inherited virtual simulation system is established. This paper studies from three levels: functional structure level, situational interaction level, information design level and cultural level. The research contents include knowledge base construction and visual teaching; Spatial simulation; Solid simulation and structure simulation; Representational guidance information and situational feedback; Intangible visual elements and immersive design of auditory media. The research of this project can be used for reference to establish a virtual simulation system of intangible cultural heritage projects with real interactive experience. Combined with the user's cognitive schema, this paper expresses the user's cognitive process and summarizes the cultural cognitive purpose to be achieved in the intangible cultural heritage digital display. Finally, the design method of intangible cultural heritage digital display based on schema theory and the construction method of digital display logic based on semantic network are proposed.

This paper focuses on the design and generation of the virtual interactive exhibition space of intangible cultural heritage, aiming to provide an innovative path for the inheritance and display of intangible cultural heritage through digital technology. Through in-depth study of the connotation and characteristics of intangible cultural heritage, combined with AR augmented reality, holographic projection, motion sensing interaction and other modern technological means, the design and generate a creative, interactive and immersive virtual display space. The design not only shows the historical origin and artistic characteristics of the intangible cultural heritage, but also emphasizes its modern value and innovative development, aiming to enhance the public's cognition and interest in the intangible cultural heritage, and promote the inheritance and development of the intangible cultural heritage. The research in this paper provides new ideas and methods for the digital protection and inheritance of intangible cultural heritage, and helps to promote the inheritance and innovation of intangible cultural heritage in modern society.

. The digital display of intangible cultural heritage is becoming increasingly important. The purpose of this study is to construct an immersive exhibition platform for intangible cultural heritage creative products using VR technology. The research utilizes methods such as virtual scene modeling and interaction design, and develops an immersive virtual exhibition hall using the example of Nanyang Duini dyeing and printing. The results show that VR technology can achieve scene reproduction and interactive experiences, effectively enhancing the sense of immersion and interactivity in exhibitions. The study demonstrates that VR is an important means for the digital display of intangible cultural heritage, providing insights for future applications. The innovation of this study lies in exploring the application of VR's immersive interactive mode in the field of cultural and creative industries.

This project reconstructs and reproduces the ecological context of “NVSHU” culture in an immersive (Virtual Reality) VR experience. We explore interactive approaches of communication for this unique intangible heritage context. "NVSHU" amplifies the effectiveness of intangible cultural heritage (ICH) preservation through narrative interaction and virtual character popularization techniques, aiming to enhance audiences’ experiential learning, and augment their sense of presence and immersion.

The "Dongba Script Character Construction Space" is an interactive science VR experience based on the Dongba script of the Naxi people in Yunnan Province, China, which provides an immersive virtual reality experience based on the traditional Yiyin script theory. [Selmanović et al., 2020] Specifically, this work combines the character construction characteristics of "pictogram", "simple ideographs" and "compound ideographs" to explore the meaning and visual symbolic characteristics of Naxi pictograms through three interesting forms of interaction, and provides more possibilities for the inheritance and development of Dongba in the future by using various forms of interaction.

Traditional puppetry is popular performing art in ancient time. However, as an intangible culture heritage, the traditional puppetry is facing the problem of losing audiences. In this paper, we present an interactive mixed-reality performance for intangible culture heritage glove puppetry. In details, we setup the performance in an history site and adopt the glove puppet performance robot to conduct the performance. Along with the interaction of professional puppeteers, audiences and the robot, the performance brings people with immersive performance experience. The mixed-reality interactions guide audiences to participate into the performance, and stir their interest in intangible culture heritage. We implemented our performance in four cases, and analyzed the immersive and interactive factors of our experiments. We hope our work can provide insights for designing culture heritage related mixed reality interactions.

As a vital component of China's intangible cultural heritage, Sichuan cuisine techniques face the risk of being lost. This paper explores the application of virtual reality and metaverse technologies in the digital preservation of Sichuan culinary skills, constructing an immersive learning platform featuring precise motion recognition, multi-sensory interaction, and physical simulation. Research findings indicate that this platform effectively enhances learning efficiency while ensuring comprehensive skill transmission—covering both explicit techniques and implicit knowledge such as temperature control and sensory judgment. Through iterative optimization, it significantly improves user experience. This digital preservation model overcomes limitations of traditional teaching methods, offering innovative approaches to safeguarding intangible cultural heritage. It holds significant implications for advancing the modernization and dissemination of traditional culinary arts.

This demonstration presents an interactive mixed reality (MR) experience utilizing HoloLens 2 to authentically simulate traditional falconry hunting, addressing the need for immersive representations of intangible cultural heritage. The project investigates how MR technologies can serve as an effective medium for preserving and conveying such practices by enabling participants to engage interactively in falconry hunting scenarios. The experience uniquely bridges historical practices with contemporary digital engagement. Designed specifically for exhibitions and cultural events, this MR experience fosters historical awareness, ecological stewardship, and inter-generational dialogue. User tests at public exhibitions demonstrated high engagement and educational value, prompting ongoing development to extend the experience to iOS platforms for broader accessibility and interaction fidelity.

As an intangible cultural heritage of China, dian cha is a unique tea-drinking ritual in traditional Chinese tea culture. The ritual comprises various tea-drinking utensils and a specific tea art performance. Nowadays, many young Chinese increasingly ignore traditional Chinese cultural activities because of their high work pressures and fast-paced lives. To broaden the audience for traditional Chinese tea ceremonies and stimulate young people’s interest in learning tea culture, we propose “DianTea” as an immersive virtual reality tea-drinking game where remote players can practice the traditional dian cha ritual. The game design also includes a virtual teacher, multimodal interaction, social scene, and game-based learning. In this paper, we also perform an intersubject user study of the game’s interactive and browsing versions. The results show that the interactive game can significantly enhance learners’ knowledge acquisition, interactive experience, and sense of participation in the dian cha ritual.

. Amidst the swift evolution of contemporary society, the age-old art of wood carving is encountering unprecedented obstacles. Powerful model rendering and detail construction were achieved using precise 3D contour details. You can see the rendering results of the complex features of the wood carving works. This article utilizes HCI-based 3D computer culture wood carving art digitization to construct an accurate model of 3D heritage wood carving. By analyzing the shape, texture, and subtle features of CAD, a 3D art woodcarving digital virtual simulation has been created in the field of digital art. The precise features of this woodcarving technique provide a more scientific platform for constructing textures. At the same time, the integration of user needs and HCI technology has created the charm of woodcarving culture and user interaction in virtual simulation spaces. By exploring the virtual influence space of intangible cultural heritage, the audience's participation and immersive experience have been increased. Created user interaction results for intangible cultural heritage woodcarving. Therefore, the seamless integration of intangible culture and virtual model simulation of wood carving into a new perspective and cutting-edge technology has been achieved.

: As one of the representatives of traditional Chinese opera, Huai Opera is an important intangible cultural heritage of the Yancheng area, whose cultural value and artistic charm face challenges in inheritance and development in the new era. The rapid development of virtual reality technology provides new possibilities for the innovative interaction and cultural transmission of Huai Opera. This paper aims to explore the strategies for the innovative interaction and transmission of Huai Opera culture in the new era based on VR technology. Through methods such as literature review, it is found that VR technology can not only effectively enhance the immersive experience of Huai Opera but also provide new paths for the global dissemination and cultural protection of Huai Opera.

The intangible cultural heritage(ICH) of China contains a wealth of oral literature. Their narrative characteristics tell the historical memory of a region or a nation. Miao ancient songs are one of them. "Dream Songs" is an immersive virtual narrative experience integrated with body interaction. Based on the singing content and antiphonal form of "Maple Song" in Miao ancient songs, our work explored the design methods of digital narrative expression of oral literature of ICH from three aspects: antiphonal interactive narrative, metaphorical body interaction, and gamification of knowledge.

Abstract Beijing Swallow Kites, one of China’s most iconic traditional crafts, hold a significant place within the country’s intangible cultural heritage (ICH). However, with rapid modernization and urbanization, the transmission of traditional kite-making skills faces severe challenges, leading to a gradual decline. To address this, we developed KiteMR, an interactive Mixed Reality (MR) system that digitally recreates this craft, offering users an immersive kite-making experience. KiteMR combines physical and digital elements with AI-assisted design, storytelling, and gamification to enhance user engagement, allowing for the creation of personalized kites. A comparative evaluation with video-based methods revealed that KiteMR significantly increased user interest in ICH, deepened their cultural understanding, and fostered emotional connections through immersive interaction. This system not only preserves and disseminates traditional craftsmanship in a digital format but also inspires deeper cultural reflection and identity.

The construction of a virtual interactive model based on VR technology breaks through the single mode of traditional virtual reality helmets, through optical attitude sensing, immersive cave virtual reality, multi-person network collaboration, 9D interactive media applications, and mobile terminal interaction. The organic integration and application of technologies have improved the user’s interactive experience, and the inheritance and development of local folk culture and the continuous research on intangible cultural heritage can be a useful exploration. However, the development cost of the entire design is relatively high, and there is no unified construction standard and policy support for such projects in China, especially the lack of effective support from the network application platform, which makes it difficult to implement online, and the reproducibility is low.

Virtual reality technology, with its immersion and interactivity, has unique advantages in cultural heritage and tourist experience promotion. However, at present, most rural tourism is still dominated by static display and one-way communication, which is difficult to stimulate tourists' enthusiasm for participation and affect the deep cultural experience. To this end, this paper constructs an innovative path of rural cultural tourism experience integrating virtual reality technology, aiming at solving the problems of fragmentation of cultural content and single experience mode. Based on cognitive psychology and virtual interaction design theory, the trinity model of “cultural node-perceived feedback-immersive interaction” is proposed, and the prototype of immersive virtual experience system is designed, and its feasibility is verified by simulation test. The research shows that this method has promotional value for the construction of digital tourism and the dissemination of intangible resources and has strong practical guiding significance.

In the context of new media, although Kunqu Opera, Peking Opera and others have been included in the Representative List of the Intangible Cultural Heritage of Humanity and dominate the national list in China, Cantonese opera is still trapped in the predicament of a shrinking market and a gap in the audience. This study takes the digital reproduction of the imperial daughter flower as the core case, uses literature analysis and deeply describes the "AI Cantonese Opera Spatio-temporal Theater", combines the theories of media convergence, cross-cultural communication, cultural adaptation and innovative diffusion, systematically sorts out the protection policies of intangible cultural heritage operas, the literature on the dissemination and technological application of Cantonese opera, and dissects the paths such as virtual set production, real-time motion capture, multilingual subtitles and immersive interaction. The results show that this set of technology can translate stylized operas into cross-media, cross-language and cross-cultural digital narratives, and promote the diffusion of technological innovation to cultural identity through digital collectibles and trend derivatives. It can thus be concluded that digital technology not only "reproduces" but also "reinterprets" the core essence of traditional opera. This has enabled Cantonese Opera to achieve a transition from a "local intangible cultural heritage" to a "global cultural language," providing a replicable paradigm for addressing challenges such as geographical limitations, language barriers, and cultural discount.

Although Jongmyo Jeryeak holds significant historical and educational value, students have limited access to its full ceremonial context and traditional instruments, which weakens their cultural connection and understanding of its significance. To address this accessibility gap, this work-in-progress presents a virtual reality rhythm game centered on Heemoon, the opening piece of the Botaepyeong suite in Jongmyo Jeryeak, to support Korean music learning and immersive cultural engagement. A prototype is developed in Unity 3D using the XR Interaction Toolkit. It features custom interaction design, audio synchronization, and a time-coded visual cue and feedback system, allowing users to interactively perform on a virtual Pyeongyeong within a recreated Jongmyo Shrine environment. By making traditional practices more accessible, this work aims to foster deeper cultural understanding among younger generations and contribute to the preservation of intangible heritage.

This paper presents a three-dimensional digital learning platform that integrates virtual reality (VR), motion capture (MoCap), and AI-assisted feedback to support the transmission of Choy Li Fut, a national item of intangible cultural heritage (ICH). Grounded in a standardized posture-format model, the platform implements four tightly coupled modules—cultural digital archiving, learning and training, immersive experience, and community interaction-connected by a closed loop of data collection, computation, feedback, evaluation, and recommendation. A mixed-method study combining knowledge quizzes, usage logs, Likert-scale surveys, interviews, and focus groups shows that while beginners attain $\mathbf{7 0 \% - 8 8 \%}$ accuracy on foundational knowledge, they continue to struggle with footwork-tactics integration, rhythm control, and hand-foot synchronization. Usage analytics indicate strong motivation $(26.7 \%$ returning two-three times per week; $46.7 \%$ registering $\gt 30$ clicks/session) but also reveal retention frictions attributable to information architecture and voice reliability. Mean satisfaction is 3.56/5 for beginners versus $3.2 / 5$ for experts, suggesting the need for tiered content depth and more advanced tactical material. We clarify the technical core of the evaluation-normalized dynamic time warping (DTW) similarity, joint-angle and angular-velocity accuracy, rhythm alignment, and a composite skill score-and outline a matched traditional-teaching baseline for validation. Contributions include (i) a computable posture-format standard for ICH martial arts, (ii) a VR-MoCap closed-loop teaching system supporting multi-stakeholder co-creation, and (iii) a reusable evaluation framework with concrete optimization routes such as adaptive progression, navigation/search refinement, AIdriven real-time error correction, and system stability improvements.

The Silk Road, spanning thousands of years, houses magnificent remnants of civilization. Among these, Silk Road mythology serves as a crucial component of intangible cultural heritage (ICH), crystallizing the primordial spirit and beliefs of diverse civilizations and offering a unique perspective for understanding a nation and its culture. However, these myths currently face challenges in preservation and dissemination. To address this, we have developed an immersive interactive system, Path of Light, that integrates artificial intelligence (AI), mixed reality (MR), and natural interaction technologies, reinterpreting the mythical bird legends from three major ancient civilizations along the Silk Road. Within this system, participants embody “Light Seekers”, traversing mythological landscapes of different civilizations alongside the bird, personally experiencing these mythological narratives while exploring their underlying cultural significance. Feedback from the pilot study demonstrates that this interactive system stimulates audience interest in Silk Road mythology and provides an innovative cross-cultural communication model and perspective for disseminating ICH.

As a vital intangible cultural heritage in the Lingnan region of China, Cantonese dragon boat culture carries profound historical memory, regional identity, and local sentiment. However, accelerated modernization has exposed this cultural legacy to risks of memory fragmentation, transmission erosion, and value distortion. This study aims to articulate the narrative of the Cantonese dragon boat tradition, reconstruct cultural memory, promote its digital and intelligent transformation, and facilitate the creative adaptation of its modern value. This study employs embodied cognition theory, cultural memory theory, and immersion theory. Through virtual reality and artificial intelligence technologies, exploring design strategies for immersive digital experiences while establishing a multi-modal interactive experience system. The research findings demonstrate that multi-modal interaction not only enhances sensory engagement and emotional resonance but also strengthens cultural recognition and identity. This study verified the effectiveness of embodied interaction-based cultural experience design and provided innovative strategies for the promotion and preservation of Cantonese dragon boat culture.

Nüshu (Jiangyong Nüshu), a script developed and practiced exclusively by women in China, holds recognition as National Intangible Cultural Heritage. This paper presents the design and implementation of an immersive multimodal interaction system centered on The Song of Nüshu, a foundational cultural artifact. By integrating Natural Interaction (NI) and Mixed Reality (MR) technologies, the system constructs a visual environment inspired by classical Chinese landscape painting aesthetics. Within this experiential space, users engage with representations of pivotal female historical figures and events interwoven with Nüshu textual elements. This framework enables participant-driven narrative construction that foregrounds Nüshu's aesthetic dimensions and socio-cultural significance. Our work advances a heritage preservation methodology that innovatively reinterprets tradition while explicitly foregrounding women's historical agency and expressive practices.

The rapid development of large language models (LLMs) has provided significant support and opportunities for the advancement of domain-specific LLMs. However, fine-tuning these large models using Intangible Cultural Heritage (ICH) data inevitably faces challenges such as bias, incorrect knowledge inheritance, and catastrophic forgetting. To address these issues, we propose a novel training method that integrates a bidirectional chains of thought and a reward mechanism. This method is built upon ICH-Qwen, a large language model specifically designed for the field of intangible cultural heritage. The proposed method enables the model to not only perform forward reasoning but also enhances the accuracy of the generated answers by utilizing reverse questioning and reverse reasoning to activate the model's latent knowledge. Additionally, a reward mechanism is introduced during training to optimize the decision-making process. This mechanism improves the quality of the model's outputs through structural and content evaluations with different weighting schemes. We conduct comparative experiments on ICH-Qwen, with results demonstrating that our method outperforms 0-shot, step-by-step reasoning, knowledge distillation, and question augmentation methods in terms of accuracy, Bleu-4, and Rouge-L scores on the question-answering task. Furthermore, the paper highlights the effectiveness of combining the bidirectional chains of thought and reward mechanism through ablation experiments. In addition, a series of generalizability experiments are conducted, with results showing that the proposed method yields improvements on various domain-specific datasets and advanced models in areas such as Finance, Wikidata, and StrategyQA. This demonstrates that the method is adaptable to multiple domains and provides a valuable approach for model training in future applications across diverse fields.

The intangible cultural heritage (ICH) of China, a cultural asset transmitted across generations by various ethnic groups, serves as a significant testament to the evolution of human civilization and holds irreplaceable value for the preservation of historical lineage and the enhancement of cultural self-confidence. However, the rapid pace of modernization poses formidable challenges to ICH, including threats damage, disappearance and discontinuity of inheritance. China has the highest number of items on the UNESCO Intangible Cultural Heritage List, which is indicative of the nation's abundant cultural resources and emphasises the pressing need for ICH preservation. In recent years, the rapid advancements in large language modelling have provided a novel technological approach for the preservation and dissemination of ICH. This study utilises a substantial corpus of open-source Chinese ICH data to develop a large language model, ICH-Qwen, for the ICH domain. The model employs natural language understanding and knowledge reasoning capabilities of large language models, augmented with synthetic data and fine-tuning techniques. The experimental results demonstrate the efficacy of ICH-Qwen in executing tasks specific to the ICH domain. It is anticipated that the model will provide intelligent solutions for the protection, inheritance and dissemination of intangible cultural heritage, as well as new theoretical and practical references for the sustainable development of intangible cultural heritage. Furthermore, it is expected that the study will open up new paths for digital humanities research.

This paper explores the integration of Artificial Intelligence (AI) in the design of interactive experiences for Cultural Heritage (CH). Previous studies indeed either miss to represent the specificity of the CH or mention possible tools without making a clear reference to a structured Interaction Design (IxD) workflow. The study also attempts to overcome one of the major limitations of traditional literature review, which may fail to capture proprietary tools whose release is rarely accompanied by academic publications. Besides the analysis of previous research, the study proposes a possible workflow for IxD in CH, subdivided into phases and tasks: for each of them, this paper proposes possible AI-based tools that can support the activity of designers, curators, and CH professionals. The review concludes with a final section outlining future paths for research and development in this domain.

Cultural heritage applications and advanced machine learning models are creating a fruitful synergy to provide effective and accessible ways of interacting with artworks. Smart audio-guides, personalized art-related content and gamification approaches are just a few examples of how technology can be exploited to provide additional value to artists or exhibitions. Nonetheless, from a machine learning point of view, the amount of available artistic data is often not enough to train effective models. Off-the-shelf computer vision modules can still be exploited to some extent, yet a severe domain shift is present between art images and standard natural image datasets used to train such models. As a result, this can lead to degraded performance. This paper introduces a novel approach to address the challenges of limited annotated data and domain shifts in the cultural heritage domain. By leveraging generative vision-language models, we augment art datasets by generating diverse variations of artworks conditioned on their captions. This augmentation strategy enhances dataset diversity, bridging the gap between natural images and artworks, and improving the alignment of visual cues with knowledge from general-purpose datasets. The generated variations assist in training vision and language models with a deeper understanding of artistic characteristics and that are able to generate better captions with appropriate jargon.

The preservation of cultural heritage faces increasing threats from climate change effects and environmental hazards, demanding innovative solutions that can promote awareness and resilience. This paper presents ARise, an Augmented Reality mobile application designed to enhance public engagement with cultural sites while raising awareness about the local impacts of climate change. Based on a user-centered co-creative methodology involving stakeholders from five European regions, ARise integrates multiple data sourcess - a Crowdsourcing Chatbot, a Social Media Data Analysis tool, and an AI-based Artwork Generation module - to deliver immersive and emotionally engaging experiences. Although formal user testing is forthcoming, this prototype demonstrates the potential of AR to support education, cultural sustainability, and climate adaptation.

The essence of intangible cultural heritage (ICH) lies in the living knowledge and skills passed down through generations. Daily practice plays a vital role in revitalizing ICH by fostering continuous learning and improvement. However, limited resources and accessibility pose significant challenges to sustaining such practice. Virtual reality (VR) has shown promise in supporting extensive skill training. Unlike technical skill training, ICH daily practice prioritizes cultivating a deeper understanding of cultural meanings and values. This study explores VR's potential in facilitating ICH daily practice through a case study of Traditional Chinese Flower Arrangement (TCFA). By investigating TCFA learners' challenges and expectations, we designed and evaluated FloraJing, a VR system enriched with cultural elements to support sustained TCFA practice. Findings reveal that FloraJing promotes progressive reflection, and continuous enhances technical improvement and cultural understanding. We further propose design implications for VR applications aimed at fostering ICH daily practice in both knowledge and skills.

Yangliuqing woodblock prints, a cornerstone of China's intangible cultural heritage, are celebrated for their intricate designs and vibrant colors. However, preserving these traditional art forms while fostering innovation presents significant challenges. This study explores the DeepSeek + MidJourney approach to generating creative, themed Yangliuqing woodblock prints focused on the fight against COVID-19 and depicting joyous winners. Using Fréchet Inception Distance (FID) scores for evaluation, the method that combined DeepSeek-generated thematic prompts, MidJourney-generated thematic images, original Yangliuqing prints, and DeepSeek-generated key prompts in MidJourney-generated outputs achieved the lowest mean FID score (150.2) with minimal variability (σ = 4.9). Additionally, feedback from 62 participants, collected via questionnaires, confirmed that this hybrid approach produced the most representative results. Moreover, the questionnaire data revealed that participants demonstrated the highest willingness to promote traditional culture and the strongest interest in consuming the AI-generated images produced through this method. These findings underscore the effectiveness of an innovative approach that seamlessly blends traditional artistic elements with modern AI-driven creativity, ensuring both cultural preservation and contemporary relevance.

Intangible Cultural Heritage (ICH) faces critical challenges in the digital age, including reduced public engagement, restricted accessibility, and difficulties in communicating complex cultural practices to modern audiences. Virtual Reality (VR) games present promising opportunities for ICH preservation and transmission, yet little is known about factors shaping their user acceptance. This study introduces a VR game centered on the Qinhuai Lantern Festival, a representative ICH case. We extend the Technology Acceptance Model (TAM) by incorporating sensory, emotional, and cultural dimensions as external variables, offering a framework for examining user acceptance of ICH-oriented VR applications. We conduct a survey with 299 respondents and apply structural equation modeling. Findings show that sensory experience significantly enhances both perceived usefulness (beta = 0.401, p < 0.001) and cultural experience (beta = 0.523, p < 0.001), while emotional experience strongly predicts positive attitudes (beta = 0.428, p < 0.001) and emotional loyalty (beta = 0.517, p < 0.001). Moreover, sensory, emotional, and cultural dimensions positively influence users' attitudes and behavioral intentions. The findings provide practical guidelines for the design of future ICH-based VR games.

Engaging in interdisciplinary projects on the intersection between visualization and humanities research can be a challenging endeavor. Challenges can be finding valuable outcomes for both domains, or how to apply state-of-the-art visual analytics methods like supervised machine learning algorithms. We discuss these challenges when working with cultural heritage data. Further, there is a gap in applying these methods to intangible heritage. To give a reflection on some interdisciplinary projects, we present three case studies focusing on the labeling of cultural heritage collections, the problems and challenges with the data, the participatory design process, and takeaways for the visualization scholars from these collaborations.

Within the cultural heritage sector, there has been a growing and concerted effort to consider a critical sociotechnical lens when applying machine learning techniques to digital collections. Though the cultural heritage community has collectively developed an emerging body of work detailing responsible operations for machine learning in libraries and other cultural heritage institutions at the organizational level, there remains a paucity of guidelines created specifically for practitioners embarking on machine learning projects. The manifold stakes and sensitivities involved in applying machine learning to cultural heritage underscore the importance of developing such guidelines. This paper contributes to this need by formulating a detailed checklist with guiding questions and practices that can be employed while developing a machine learning project that utilizes cultural heritage data. I call the resulting checklist the "Collections as ML Data" checklist, which, when completed, can be published with the deliverables of the project. By surveying existing projects, including my own project, Newspaper Navigator, I justify the "Collections as ML Data" checklist and demonstrate how the formulated guiding questions can be employed and operationalized.

This paper introduces a pipeline for integrating semantic metadata, 3D models, and storytelling, enhancing cultural heritage digitization. Using the Aldrovandi Digital Twin case study, it outlines a reusable workflow combining RDF-driven narratives and data visualization for creating interactive experiences to facilitate access to cultural heritage.

In this paper, we present a case study exploring the potential use of Generative Artificial Intelligence (GAI) to address the real-world need of making the design of embroiderable art patterns more accessible. Through an auto-ethnographic case study by a disabled-led team, we examine the application of GAI as an assistive technology in generating embroidery patterns, addressing the complexity involved in designing culturally-relevant patterns as well as those that meet specific needs regarding detail and color. We detail the iterative process of prompt engineering custom GPTs tailored for producing specific visual outputs, emphasizing the nuances of achieving desirable results that align with real-world embroidery requirements. Our findings underscore the mixed outcomes of employing GAI for producing embroiderable images, from facilitating creativity and inclusion to navigating the unpredictability of AI-generated designs. Future work aims to refine GAI tools we explored for generating embroiderable images to make them more performant and accessible, with the goal of fostering more inclusion in the domains of creativity and making.

The rapid advancement of Information and Communication Technologies is transforming Cultural Heritage access, experience, and preservation. However, many digital heritage applications lack interactivity, personalization, and adaptability, limiting user engagement and educational impact. This short paper presents a reference architecture for gamified cultural heritage applications leveraging generative AI and augmented reality. Gamification enhances motivation, artificial intelligence enables adaptive storytelling and personalized content, and augmented reality fosters immersive, location-aware experiences. Integrating AI with gamification supports dynamic mechanics, personalized feedback, and user behavior prediction, improving engagement. The modular design supports scalability, interoperability, and adaptability across heritage contexts. This research provides a framework for designing interactive and intelligent cultural heritage applications, promoting accessibility and deeper appreciation among users and stakeholders.

Material heritage typically has a whole set of associated immaterial heritage, which is essential to pass on to the visitor as a cultural mission of the destinations and those who manage them. In this sense, the interpretation of material heritage is a complex process that is not a fully efficient process with the mere observation of physical artifacts. In this context, it emerges as fundamental to provide visitors with a set of tools that allow them to correctly interpret the artifacts that come to fully understand the cultural dimension of the destinations and their heritage. Accordingly, the role of virtual reality can leverage the creation of innovative and immersive solutions that allow the visitor to understand and feel part of their own heritage and its ancestral component that defines the sociocultural roots of destinations and their civilizational traditions. This article, after dissecting and substantiating the role of virtual reality in the interpretation of heritage, presents a conceptual model, based on the use of virtual reality, which was, in part, prototyped in the scenario of the Portuguese Museum in the city of Miranda do Douro. This proposal is an ongoing contribution to the creation of innovative and immersive tools for the interpretation of heritage.