ICA-FX features for classification of singing voice and instrumental sound

• Main Authors: LEUNG, Tat-Wan, NGO, Chong-wah, LAU, Rynson W. H
• Format: text
• Language: English
• Published: Institutional Knowledge at Singapore Management University 2004
• Subjects: Computer Sciences; Graphics and Human Computer Interfaces
• Online Access: https://ink.library.smu.edu.sg/sis_research/6488; https://ink.library.smu.edu.sg/context/sis_research/article/7491/viewcontent/icpr04_b.pdf
• Institution: Singapore Management University

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.