Abstract
Machine learning is the core field of artificial intelligence. It provides a guarantee for the digital intangible cultural heritage management of artificial intelligence. However, the existing theoretical and practical research points out that there are still many gaps in this field. Huaer is a folk song popular in Qinghai, Gansu, Ningxia Hui Autonomous Region, and individual regions of Xinjiang. It is known as the soul of the northwest. It is a national human intangible cultural heritage. It was listed as human intangible cultural heritage by the United Nations in September 2009. With the rapid development of network technology and machine learning, it is very important to manage the network communication and deep mining of Huaer information. In this regard, use of machine learning natural language processing to mine the information of Huaer lyrics is proposed. By constructing the Huaer model of recurrent neural network (RNN), data mining of Huaer lyrics is carried out, and the built-in language module in Python is interconnected with dynamic Web pages. Four Huaer image segmentation methods and five deep learning algorithms are proposed, and the steps of image segmentation algorithm and BP neural network algorithm based on block technology are introduced. The results can provide new ideas for the protection and inheritance of music intangible cultural heritage and provide effective and high-quality information for Huaer art researchers and lovers.
Highlights
Artificial intelligence is the greatest scientific and technological innovation in the 21st century [1,2,3,4,5]
As the core field of artificial intelligence, the goal of machine learning is to let computers learn by themselves. e machine learning algorithm enables it to identify the laws in the observation data, build a model to explain the world, and predict things without clear preprogramming rules and models [6,7,8,9]
How to identify intangible cultural heritage with the help of machine learning, build a model to explain the characteristics of Huaer music, and inherit intangible cultural heritage with artificial intelligence is an urgent practical problem in front of the academic interface
Summary
Artificial intelligence is the greatest scientific and technological innovation in the 21st century [1,2,3,4,5]. How to identify intangible cultural heritage with the help of machine learning, build a model to explain the characteristics of Huaer music, and inherit intangible cultural heritage with artificial intelligence is an urgent practical problem in front of the academic interface. From the perspective of machine learning, this study examines and discusses the identification of Huaer, the world intangible cultural heritage. Except for a few studies that have developed the emotion recognition system of music audio, most studies focus on audio pitch recognition and note recognition, while there are few empirical studies on Huaer case base based on machine learning, only the regional pattern classification of Chinese folk songs [14,15,16,17]. Erefore, from the perspective of machine learning, this study introduces musicology, computer science, and technology to explore the construction of Huaer resource database, to summarize various algorithms and strategies of Huaer recognition No one has set foot in the field of introducing machine learning into Huaer recognition research. erefore, from the perspective of machine learning, this study introduces musicology, computer science, and technology to explore the construction of Huaer resource database, to summarize various algorithms and strategies of Huaer recognition
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