Musical structural segmentation methods based on sound descriptors
Author: André Salim Pires
Advisor: Marcelo Queiroz
Project description
In this project, a comparative study of different music structural segmentation methods is presented, where the goal is to delimit the borders of musical sections and label them, i.e. group the sections that correspond to the same musical part. Novel proposals for unsupervised segmentation are presented, including methods for real-time segmentation, achieving expressive results, with error ratio less then 12%. Our method consists of a study of sound descriptors, an exposition of the computational techniques for structural segmentation and the description of the evaluation methods utilized, which penalize both incorrect boundary detection and incorrect number of labels. The performance of each technique is calculated using different sound descriptor sets and the results are presented and analysed both from quantitative and qualitative points-of-view.
Keywords
music information retrieval, music structural segmentation, real-time music segmentation, generation and selection of sound descriptors, real-time sound processing.
Implementation
The code is available in http://code.google.com/p/umslt. For more information please contact the author.
Resources
Contact
- André S. Pires.
- andrespires@gmail.com