Autonomous driving paper index
Research on the Digital Activation and Innovative Dissemination of Zhaoqing Folk Songs in China Empowered by Artificial Intelligence: A Case Study of `Yuanlongling Hakka Mountain Songs'
One-line summary
Under the contemporary backdrop of rapid digital technology iteration, artificial intelligence (AI) music technology has emerged as a crucial means for the creative transformation and innovative development of traditional intangible cultural heritage (ICH) music.
Engineering notes
This process significantly enhances the acoustic texture, stage visual appeal, and cross-media adaptability of local folk songs, helping construct a multi-dimensional and modernized dissemination system.
Chinese explanation / 中文解读
中文解读待补充：本站会优先为端到端自动驾驶、BEV感知、3D目标检测、轨迹预测、路径规划、LiDAR感知等高价值论文补充中文说明。
Original abstract
Under the contemporary backdrop of rapid digital technology iteration, artificial intelligence (AI) music technology has emerged as a crucial means for the creative transformation and innovative development of traditional intangible cultural heritage (ICH) music. This article examines the digital revitalization and innovative dissemination of Zhaoqing folk songs in China, utilizing the `Yuanlongling Hakka Mountain Songs' as a core case study. Integrating AI-assisted creative practice with case-based reflection, this study explores the algorithmic sound generation, platformized circulation, and contemporary revitalization of local folk music, focusing on the `Yuanlongling Hakka Mountain Songs' of Zhaoqing, China. The analysis demonstrates that AI technology does not dissolve the regional cultural characteristics of traditional folk songs; rather, under manual aesthetic control, it compensates for the limitations of traditional music production through efficient and controllable digital means. This process significantly enhances the acoustic texture, stage visual appeal, and cross-media adaptability of local folk songs, helping construct a multi-dimensional and modernized dissemination system. By documenting this specific case of technological mediation, the study offers practical insights into how interactive human-AI workflows can adapt local musical traditions for contemporary digital culture.
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