The Current Status and Challenges of Chinese Folk Music Preservation and Transmission

Chinese folk music, originating from real life and grassroots communities, often features rich forms and humorous content, possessing invaluable historical, cultural, and artistic value.This study aims to promote the inheritance and development of Chinese folk music by designing a user needs survey questionnaire for a digital learning resource repository of Chinese folk music, summarizing its current development status and the challenges it faces.Given the diversity and irregularity of Chinese folk music entities, a music named entity recognition model is constructed with a main structure comprising a representation layer, a TDCNN encoding layer, a recurrent network layer, and a prediction layer, specifically for entity recognition in the field of Chinese folk music.Additionally, a link prediction model based on feature mapping and bidirectional convolution is established to achieve mapping conversion between entities and relationships, thereby uncovering their subtle connections.By integrating the two models, a folk music relationship extraction model is proposed to provide technical support for the establishment of a Chinese folk digital learning resource repository.In comparative experiments with various similar models, this model demonstrated the highest accuracy rate (99.08%) and F1 score (97.17%), showing high compatibility with the requirements of Chinese folk music relationship extraction tasks.

Publication Details

Journal
International journal for housing science and its applications.
Published
2025-08-15
DOI
https://doi.org/10.70517/ijhsa464238
Primary Topic
Asian Culture and Media Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

The Current Status and Challenges of Chinese Folk Music Preservation and Transmission

International journal for housing science and its applications.
Asian Culture and Media Studies
article

The Current Status and Challenges of Chinese Folk Music Preservation and Transmission

article en

Abstract

Chinese folk music, originating from real life and grassroots communities, often features rich forms and humorous content, possessing invaluable historical, cultural, and artistic value.This study aims to promote the inheritance and development of Chinese folk music by designing a user needs survey questionnaire for a digital learning resource repository of Chinese folk music, summarizing its current development status and the challenges it faces.Given the diversity and irregularity of Chinese folk music entities, a music named entity recognition model is constructed with a main structure comprising a representation layer, a TDCNN encoding layer, a recurrent network layer, and a prediction layer, specifically for entity recognition in the field of Chinese folk music.Additionally, a link prediction model based on feature mapping and bidirectional convolution is established to achieve mapping conversion between entities and relationships, thereby uncovering their subtle connections.By integrating the two models, a folk music relationship extraction model is proposed to provide technical support for the establishment of a Chinese folk digital learning resource repository.In comparative experiments with various similar models, this model demonstrated the highest accuracy rate (99.08%) and F1 score (97.17%), showing high compatibility with the requirements of Chinese folk music relationship extraction tasks.

International journal for housing science and its applications.Vol. 46(4)
Openalex Percentile: Top 74%
Asian Culture and Media Studies
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