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Benchmarking Dynamic Time Warping for Music Retrieval Jefrey Lijffijt1,2
 

Summary: Benchmarking Dynamic Time Warping for Music Retrieval
Jefrey Lijffijt1,2
, Panagiotis Papapetrou1,2
, Jaakko Hollmén1,2
, and Vassilis Athitsos3
1
Department of Information and Computer Science, Aalto University School of Science and Technology, Finland
2
Helsinki Institute for Information Technology, Finland
3
Computer Science and Engineering Department, University of Texas at Arlington, USA
ABSTRACT
We study the performance of three dynamic programming
methods on music retrieval. The methods are designed for
time series matching but can be directly applied to retrieval
of music. Dynamic Time Warping (DTW) identifies an op-
timal alignment between two time series, and computes the
matching cost corresponding to that alignment. Significant
speed-ups can be achieved by constrained Dynamic Time
Warping (cDTW), which narrows down the set of positions

  

Source: Athitsos, Vassilis - Department of Computer Science and Engineering, University of Texas at Arlington

 

Collections: Computer Technologies and Information Sciences