DocumentCode :
1558342
Title :
Structural Segmentation of Multitrack Audio
Author :
Hargreaves, Steven ; Klapuri, Anssi ; Sandler, Mark
Author_Institution :
Centre for Digital Music, Department of Electronic Engineering, Queen Mary University of London, London, UK
Volume :
20
Issue :
10
fYear :
2012
Firstpage :
2637
Lastpage :
2647
Abstract :
Structural segmentation of musical audio signals is one of many active areas of Music Information Retrieval (MIR) research. One aspect of this important topic which has so far received little attention though is the potential advantage to be gained by utilizing multitrack audio. This paper gives an overview of current segmentation techniques, and demonstrates that by applying a particular segmentation algorithm to multitrack data, rather than the usual case of fully mixed audio, we achieve a significant and quantifiable increase in accuracy when locating segment boundaries. Additionally, we provide details of a structurally annotated multitrack test set available for use by other researchers.
Keywords :
Feature extraction; Indexes; Music information retrieval; Signal processing algorithms; Timbre; Audio; multitrack; music information retrieval (MIR); structural segmentation;
fLanguage :
English
Journal_Title :
Audio, Speech, and Language Processing, IEEE Transactions on
Publisher :
ieee
ISSN :
1558-7916
Type :
jour
DOI :
10.1109/TASL.2012.2209419
Filename :
6243190
Link To Document :
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