Music Rearrangement Using Hierarchical Segmentation

• Published in: Proceedings of the ... IEEE International Conference on Acoustics, Speech and Signal Processing (1998) pp. 1 - 5
• Main Authors: Plachouras, Christos, Miron, Marius
• Format: Conference Proceeding
• Language: English
• Published: IEEE 04.06.2023
• Subjects: Acoustics; Multiple signal classification; music rearrangement; music segmentation; music structure analysis; path finding; Recording; spectral clustering; Speech processing; Task analysis
• ISSN: 2379-190X
• DOI: 10.1109/ICASSP49357.2023.10097212

Music rearrangement involves reshuffling, deleting, and repeating sections of a music piece with the goal of producing a standalone version that has a different duration. It is a creative and time-consuming task commonly performed by an expert music engineer. In this paper, we propose a method for automatically rearranging music recordings that takes into account the hierarchical structure of the recording. Previous approaches focus solely on identifying cut-points in the audio that could result in smooth transitions. We instead utilize deep audio representations to hierarchically segment the piece and define a cut-point search subject to the boundaries and musical functions of the segments. We score suitable entry-and exit-point pairs based on their similarity and the segments they belong to, and define an optimal path search. Experimental results demonstrate the selected cut-points are most commonly imperceptible by listeners and result in more consistent musical development with less distracting repetitions.