AI-GENERATED FOLK MUSIC AND ITS CULTURAL RELEVANCE

Authors

  • Dr. Santanu Kumar Sahoo Associate Professor, Department of Electronics and Communication Engineering, Institute of Technical Education and Research, Siksha 'O' Anusandhan (Deemed to be University) Bhubaneswar, Odisha, India
  • Ramneek Kelsang Bawa Assistant Professor, School of Business Management, Noida international University 203201
  • Hitesh Kalra Chitkara Centre for Research and Development, Chitkara University, Himachal Pradesh, Solan, 174103, India
  • Dr. Priti Shende ssociate Professor, Electronics &Telecommunication, Dr. D.Y.Patil Institute of Technology ,Pimpri,Pune.
  • Megha Jagga Centre of Research Impact and Outcome, Chitkara University, Rajpura- 140417, Punjab, India
  • Dr. Sivasangari A Professor, Department of Computer Science and Engineering, Sathyabama Institute of Science and Technology, Chennai, Tamil Nadu, India

DOI:

https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6724

Keywords:

AI-Generated Folk Music, Cultural Relevance, Transformer Models, The Folk Music Preservation, Authenticity Assessment, Cultural Ethics in AI and The Community Perception, Generative Music Systems

Abstract [English]

Artificial Intelligence (AI) has rapidly become a means to create music similar to the traditional cultural forms, but its impact on folk music as a form of art that is developed through oral tradition, community identity, and ritual sense has not been properly studied. The cultural relevance of AI-generated folk music, technical performance, and ethical implications of the technology will be explored in this paper in three folk traditions: Irish reels and jigs, Indian Garba/Lavani, and West African drumming. With the help of transformer, diffusion, and GAN-based models trained on culturally diverse samples, the study compares the outputs by using melodic, rhythmic, timbral, and cultural coherence metrics and additional community and expert evaluation. Findings indicate that AI can be used successfully in notation-friendly and structurally regular traditions and is weak in microtonality, expressive ornamentation, and rhythmic interaction of an ensemble. An important gap in perception is revealed: the listeners who listen to the music produced by AI have a more positive attitude to it, but those who belong to the traditions see cultural and stylistic mistakes. Ethical risks such as cultural misrepresentation, ownership and sensitivity in sacred material increase in highly culturally deprived traditions. The paper claims that AI can facilitate conservation and creative reuse in the event of ethical design, involvement in community, and culturally aware data. It ends by suggesting an ethically correct AI integration model that is culturally sensitive in folk music systems.

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Published

2025-12-16

How to Cite

Sahoo, . S. K., Bawa, R. K., Kalra, H., Shende, P., Jagga, M., & Sivasangari A. (2025). AI-GENERATED FOLK MUSIC AND ITS CULTURAL RELEVANCE. ShodhKosh: Journal of Visual and Performing Arts, 6(2s), 219–229. https://doi.org/10.29121/shodhkosh.v6.i2s.2025.6724