Package for the segmentation of autosimilarity matrices.
Project description
as_seg: module for computing and segmenting autosimilarity matrices.
Hello, and welcome on this repository!
This project aims at computing autosimilarity matrices, and segmenting them, which consists of the task of structural segmentation.
The current version contains the CBM algorithm [1], along with a (low-effort) implementation of Foote's novelty algorithm [2].
This is a first release, and may contain bug. Comments are welcomed!
Tutorial notebook
A tutorial notebook presenting the most important components of this toolbox is available in the folder "Notebooks" (called "Walkthrough").
Software version
This code was developed with Python 3.8.5, and some external libraries detailed in dependencies.txt. They should be installed automatically if this project is downloaded using pip.
Credits
Code was created by Axel Marmoret (axel.marmoret@irisa.fr), and strongly supported by Jeremy E. Cohen (jeremy.cohen@cnrs.fr).
The technique in itself was also developed by Frédéric Bimbot (bimbot@irisa.fr).
References
[1] Marmoret, A., Cohen, J. E., & Bimbot, F., "Convolutive Block-Matching Segmentation Algorithm with Application to Music Structure Analysis", 2022, arXiv preprint arXiv:2210.15356.
[2] Foote, J., "Automatic audio segmentation using a measure of audio novelty", in: 2000 IEEE Int. Conf. Multimedia and Expo. ICME2000. Proc. Latest Advances in the Fast Changing World of Multimedia, vol. 1, IEEE, 2000,pp. 452–455.
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