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Automatic Structure Detection for Popular Music
January-March 2006 (vol. 13 no. 1)
pp. 65-77
ASCII Text
x 
 
Namunu C. Maddage, "Automatic Structure Detection for Popular Music," IEEE Multimedia, vol. 13, no. 1, pp. 65-77, January-March, 2006.
 
 
BibTex
x
 
@article{ 10.1109/MMUL.2006.3,
author = {Namunu C. Maddage},
title = {Automatic Structure Detection for Popular Music},
journal ={IEEE Multimedia},
volume = {13},
number = {1},
issn = {1070-986X},
year = {2006},
pages = {65-77},
doi = {http://doi.ieeecomputersociety.org/10.1109/MMUL.2006.3},
publisher = {IEEE Computer Society},
address = {Los Alamitos, CA, USA},
}
 
 
RefWorks Procite/RefMan/Endnote
x 
 
TY - MGZN
JO - IEEE Multimedia
TI - Automatic Structure Detection for Popular Music
IS - 1
SN - 1070-986X
SP65
EP77
EPD - 65-77
A1 - Namunu C. Maddage,
PY - 2006
KW - segmentation
KW - voice boundaries
KW - content-based
KW - octaves
KW - subbands
VL - 13
JA - IEEE Multimedia
ER -
 
Namunu C. Maddage, Institute for Infocomm Research
Our proposed approach detects music structures by looking at beat space segmentation, chords, singing-voice boundaries, and melody- and content-based similarity regions. Experiments illustrate that the proposed approach is capable of extracting useful information for music applications.
Index Terms:
segmentation, voice boundaries, content-based, octaves, subbands
Citation:
Namunu C. Maddage, "Automatic Structure Detection for Popular Music," IEEE Multimedia, vol. 13, no. 1, pp. 65-77, Jan.-Mar. 2006, doi:10.1109/MMUL.2006.3
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