Intangible Cultural Heritage in China: A Visual Analysis of Research Hotspots, Frontiers, and Trends Using CiteSpace

Dang, Qiong; Luo, Zhongming; Ouyang, Chuhao; Lin, Wang; Xie, Mei

doi:10.3390/su13179865

Cited by 36 publications

(24 citation statements)

References 53 publications

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“…The development of grassland ecotourism can not only provide necessary material support for the protection of Mongolian intangible cultural heritage, but also provide a realistic need for the existence of intangible cultural heritage. Correctly handling the relationship between the development of grassland tourism and strengthening the protection of the intangible cultural heritage of ethnic minorities is very significant to achieve a win-win situation between the development of grassland ecotourism and the protection of Mongolian intangible cultural heritage [ 3 , 4 ].…”

Section: Introductionmentioning

confidence: 99%

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture

Bu¹,

Jiang

2022

Computational Intelligence and Neuroscience

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Inner Mongolia is rich in grassland tourism resources, and the development of grassland tourism is of great significance to Inner Mongolia tourism and promotion of grassland protection. To better promote the grassland tourism of the Silk Road culture, the Conditional Global Area Network (CGAN) and Morphology Connected Component Chan-Vase (MCC-CV) algorithm are used to enhance and segment the traditional embroidery patterns in Inner Mongolia. Firstly, the generative adversarial network (GAN) is optimized, and a new GAN is proposed with the feature vector extracted from the convolutional neural network (CNN) as the constraint condition. Secondly, the automatic segmentation algorithm of embroidery based on the MCC-CV model is proposed, and finally, the proposed algorithm is tested. The test results demonstrate that after 8000 iterations of the proposed image-enhancement algorithm, its personalized features are enhanced, and the segmentation accuracy of the proposed image segmentation algorithm is 60%. The proposed algorithm provides some ideas for the application of deep learning (DL) technology in the grassland tourism of the Silk Road culture and also helps operators to accurately grasp the market and make tourists more comfortable and pleasant.

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Section: Introductionmentioning

confidence: 99%

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture

Bu¹,

Jiang

2022

Computational Intelligence and Neuroscience

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“…To date, 42 of China's ICH items have been inscribed on UNESCO's Representative List of the Intangible Cultural Heritage of Humanity, making it the country with the most ICH in the world. Notably, China's Kunqu Opera was first inscribed in 2001, marking the entry of China's ICH onto the world stage [64]. As an outstanding representative of traditional Chinese theatre, a Kunqu Opera performance is a comprehensive art that includes singing, reciting, acting, playing and dancing, which makes it highly enjoyable and experiential.…”

Section: Methods 41 Research Objectmentioning

confidence: 99%

Perceived Authenticity and Experience Quality in Intangible Cultural Heritage Tourism: The Case of Kunqu Opera in China

Yong-jun

et al. 2022

Sustainability

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In the era of the experience economy, intangible cultural heritage (ICH) is now much a richer in terms of authenticity, which largely enriches the tourist experience. This study aims to apply authenticity theory to the field of intangible cultural heritage tourism (ICHT) and to analyze the relationship between the dual dimensions of tourists’ perceived authenticity (constructivism and existentialism) and experience quality and satisfaction. A total of 302 valid questionnaires were collected and analyzed using structural equation modeling through a survey of Kunqu Opera, a World ICH in China. The results of this study confirm that the dual dimensions of authenticity (constructive and existential) have significantly different effects on experience quality and satisfaction. Furthermore, with regard to the mediating effect of experience quality, experience quality plays a partially mediating role between existential authenticity and satisfaction. However, constructive authenticity is a positive influence on satisfaction through existential authenticity and experience quality. This article is concluded with a discussion on the theoretical and managerial implications.

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“…It belongs to the frequency-domain features, is mainly used for audio data feature extraction and reduces the dimension of operation. The correspondence between Mel frequency and Hz frequency is shown in Equation (3). And the frequency-domain features of relevant signal can be calculated through the mapping relationship between the two frequencies.…”

Section: Mel-frequency Cepstrummentioning

confidence: 99%

“…Taking advantage of artificial intelligence technology to rescue, excavate, organize, protect and disseminate traditional culture has become the direction of intangible cultural heritage conservation today [1,2]. Besides, studying the intelligent development of intangible cultural heritage will also become an essential issue in the heritage of contemporary excellent traditional culture in China [3,4]. In the art of Cantonese opera, singing music is an important means of shaping characters and expressing the happiness, anger and sorrow of the characters.…”

Section: Introductionmentioning

confidence: 99%

The Sustainable Development of Intangible Cultural Heritage with AI: Cantonese Opera Singing Genre Classification Based on CoGCNet Model in China

Chen

Zhao

Wang³

et al. 2022

Sustainability

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Chinese Cantonese opera, a UNESCO Intangible Cultural Heritage (ICH) of Humanity, has faced a series of development problems due to diversified entertainment and emerging cultures. While, the management on Cantonese opera data in a scientific manner is conducive to the sustainable development of ICH. Therefore, in this study, a scientific and standardized audio database dedicated to Cantonese opera is established, and a classification method for Cantonese opera singing genres based on the Cantonese opera Genre Classification Networks (CoGCNet) model is proposed given the similarity of the rhythm characteristics of different Cantonese opera singing genres. The original signal of Cantonese opera singing is pre-processed to obtain the Mel-Frequency Cepstrum as the input of the model. The cascade fusion CNN combines each segment’s shallow and deep features; the double-layer LSTM and CNN hybrid network enhance the contextual relevance between signals. This achieves intelligent classification management of Cantonese opera data, meanwhile effectively solving the problem that existing methods are difficult to classify accurately. Experimental results on the customized Cantonese opera dataset show that the method has high classification accuracy with 95.69% Precision, 95.58% Recall and 95.60% F1 value, and the overall performance is better than that of the commonly used neural network models. In addition, this method also provides a new feasible idea for the sustainable development of the study on the singing characteristics of the Cantonese opera genres.

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Intangible Cultural Heritage in China: A Visual Analysis of Research Hotspots, Frontiers, and Trends Using CiteSpace

Cited by 36 publications

References 53 publications

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture

Extraction of Intangible Cultural Heritage Visual Elements by Deep Learning and Its Application in Grassland Tourism of the Silk Road Culture

Perceived Authenticity and Experience Quality in Intangible Cultural Heritage Tourism: The Case of Kunqu Opera in China

The Sustainable Development of Intangible Cultural Heritage with AI: Cantonese Opera Singing Genre Classification Based on CoGCNet Model in China

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