Post-AI
Human Cognitive Study on Artificial Intelligence for Music
Hyunjae Kim, Eunji Oh, Kyung Myun Lee
Recently, automatic composition models based on artificial intelligence (AI) techniques have made it possible to automatically generate musical melodies in the style of various artists. The significance of human assessment of musical similarity between original and AI-generated music in the context of copyright issues has been widely acknowledged. Nevertheless, despite the significance of perceptual similarity, this aspect has yet to be thoroughly examined. In this study, we explore the intersection of human cognition and artificial intelligence in music.
- Kim, H. J., Choi, E. J., Oh, E. J, Nam, J. H. & Lee, K. M. (2023). *Evaluation of AI-generated Music through Online Surveys*, Korean Society for Music Perception and Cognition (KSMPC). [Link]
- Kim, H. J., Oh, E. J, Park, J. E., Chung, Y. J., Nam, J. H. & Lee, K. M. (2023). *A comparison of melody interpolation performed by human and artificial intelligence based on human similarity judgments*, The [17th International Conference on Music Perception and Cognition](https://jsmpc.org/ICMPC17/) (ICMPC). [Link]
- Kim, H. J., Oh, E. J, Chung, Y. J., Nam, J. H. & Lee, K. M. (2023). *A study of melody similarity of AI-composition with cognitive behavioral experiment*, Korean Society for Music Perception and Cognition (KSMPC).
Funding
KAIST Post-AI Research