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Proceedings Paper

Content-based retrieval of music and audio
Author(s): Jonathan T. Foote
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Paper Abstract

Though many systems exist for content-based retrieval of images, little work has been done on the audio portion of the multimedia stream. This paper presents a system to retrieve audio documents y acoustic similarity. The similarity measure is based on statistics derived from a supervised vector quantizer, rather than matching simple pitch or spectral characteristics. The system is thus able to learn distinguishing audio features while ignoring unimportant variation. Both theoretical and experimental results are presented, including quantitative measures of retrieval performance. Retrieval was tested on a corpus of simple sounds as well as a corpus of musical excerpts. The system is purely data-driven and does not depend on particular audio characteristics. Given a suitable parameterization, this method may thus be applicable to image retrieval as well.

Paper Details

Date Published: 6 October 1997
PDF: 10 pages
Proc. SPIE 3229, Multimedia Storage and Archiving Systems II, (6 October 1997); doi: 10.1117/12.290336
Show Author Affiliations
Jonathan T. Foote, National Univ. of Singapore (Singapore)


Published in SPIE Proceedings Vol. 3229:
Multimedia Storage and Archiving Systems II
C.-C. Jay Kuo; Shih-Fu Chang; Venkat N. Gudivada, Editor(s)

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