Publication Type
Conference Proceeding Article
Version
publishedVersion
Publication Date
8-2004
Abstract
This paper describes a new approach in locating the segments of singing voice in pop musical songs. Initially, GLR distance measure is employed to temporally detect the boundaries of singing voices and instrumental sounds. ICAFX is then adopted to extract the independent components of acoustic features for SVM classification. Experimental results indicate that ICA-FX can improve the classification performance by significantly reducing the independent components that are not related to class label information.
Discipline
Computer Sciences | Graphics and Human Computer Interfaces
Research Areas
Intelligent Systems and Optimization
Publication
Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, 2004 August 23-26
Volume
2
First Page
367
Last Page
370
ISBN
0769521282
Identifier
10.1109/ICPR.2004.1334222
Publisher
IEEE
City or Country
Cambridge
Citation
LEUNG, Tat-Wan; NGO, Chong-wah; and LAU, Rynson W. H.
ICA-FX features for classification of singing voice and instrumental sound. (2004). Proceedings of the 17th International Conference on Pattern Recognition, ICPR 2004, Cambridge, UK, 2004 August 23-26. 2, 367-370.
Available at: https://ink.library.smu.edu.sg/sis_research/6488
Creative Commons License
This work is licensed under a Creative Commons Attribution-NonCommercial-No Derivative Works 4.0 International License.