NDLI: GPU-Accelerated Query by Humming Using Modified SPRING Algorithm

Content Provider	IEEE Xplore Digital Library
Author	Guangchao Yao Yao Zheng Limin Xiao Li Ruan Yongnan Li Zhenzhong Zhang
Copyright Year	2013
Description	Author affiliation: State Key Lab. of Software Dev. Environ., Beihang Univ., Beijing, China (Guangchao Yao; Yao Zheng; Limin Xiao; Li Ruan; Yongnan Li; Zhenzhong Zhang)
Abstract	Current query by humming system can hardly be extended to large massive database as most of them adopt the features extracted from MIDI files which are not widely used and the very time-consuming match methods. In this work, we regard query by humming as a subsequence similarity match problem and exploit the modified SPRING algorithm instead of DTW as the core match method to compare the melody feature extracted from polyphonic music. The SPRING algorithm reduces the algorithm complexity of subsequence match dramatically. Furthermore, we also make it possible for our system to achieve a high speedup over the serial version on different GPU platforms. Experimental results show that our system has more advantages over the state of the art subsequence match method, and has a good scalability to massive database. The processing capacity can reach to thousands of sequences match per second under down sampling. At the same time, the retrieval accuracy results related to all aspects of query by humming point out the encountered problems and the future direction.
Sponsorship	Toshiba
Starting Page	654
Ending Page	663
File Size	387447
Page Count	10
File Format	PDF
e-ISBN	9781479931422
DOI	10.1109/ICDMW.2013.104
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2013-12-07
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Accuracy SPRING Databases Music Graphics processing units Feature Extraction Feature extraction Acceleration Springs GPU Query by Humming
Content Type	Text
Resource Type	Article

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