Huge music archives on mobile devices: toward an automated dynamic organization

H. Blume, B. Bischl, M. Botteck, Christian Igel, R. Martin, G. Rötter, G. Rudolph, W. Theimer, I. Vatolkin, C. Weihs

Research output: Contribution to journalJournal articleResearchpeer-review

7 Citations (Scopus)

Abstract

The availability of huge nonvolatile storage capacities such as flash memory allows large music archives to be maintained even in mobile devices. With the increase in size, manual organization of these archives and manual search for specific music becomes very inconvenient. Automated dynamic organization enables an attractive new class of applications for managing ever-increasing music databases. For these types of applications, extraction of music features as well as subsequent feature processing and music classification have to be performed. However, these are computationally intensive tasks and difficult to tackle on mobile platforms. Against this background, we provided an overview of algorithms for music classification as well as their computation times and other hardware-related aspects, such as power consumption on various hardware architectures. For mobile platforms such as smartphones, a careful balance of algorithm complexity, hardware architecture, and classification accuracy has to be found to provide a high quality user experience.

Original languageEnglish
JournalIEEE Signal Processing Magazine
Volume28
Issue number4
Pages (from-to)24-39
Number of pages16
DOIs
Publication statusPublished - 2011

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