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http://dx.doi.org/10.9728/dcs.2017.18.5.811

A Content-based Audio Retrieval System Supporting Efficient Expansion of Audio Database  

Park, Ji Hun (Department of of Computer Science and Engineering, Graduate School, Chung-Ang University)
Kang, Hyunchul (School of of Computer Science and Engineering, Chung-Ang University)
Publication Information
Journal of Digital Contents Society / v.18, no.5, 2017 , pp. 811-820 More about this Journal
Abstract
For content-based audio retrieval which is one of main functions in audio service, the techniques for extracting fingerprints from the audio source, storing and indexing them in a database are widely used. However, if the fingerprints of new audio sources are continually inserted into the database, there is a problem that space efficiency as well as audio retrieval performance are gradually deteriorated. Therefore, there is a need for techniques to support efficient expansion of audio database without periodic reorganization of the database that would increase the system operation cost. In this paper, we design a content-based audio retrieval system that solves this problem by using MapReduce and NoSQL database in a cluster computing environment based on the Shazam's fingerprinting algorithm, and evaluate its performance through a detailed set of experiments using real world audio data.
Keywords
Cluster computing environment; Content-based music retrieval system; Digital audio source; MapReduce; NoSQL database;
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Times Cited By KSCI : 2  (Citation Analysis)
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