An evaluation of feature extraction for query-by-content audio information retrieval

Yi Yu, J. Stephen Downie, Kazuki Joe

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Content-based audio information retrieval is one of the most interesting and fast-growing research areas. Suitable feature sets can help to reduce the tedious computation time and speed up retrieval. In this paper we report a study of the music spectral properties aimed at the acoustic-based music data similarity measurement and show that the spectral features of adjacent frames are highly correlated. Based on such a case study we mainly focus on making an evaluation of feature choice in the three aspects: storage, computation and retrieval ratio. The extensive evaluations confirm the effectiveness of feature merge in quickening sequence matching for query-by-content audio retrieval and show that MFCC with feature merge is the best tradeoff among storage requirement, computation cost and retrieval ratio.

Original languageEnglish (US)
Title of host publicationProceedings ISM Workshops 2007 - 9th IEEE International Symposium on Multimedia - Workshops
Pages297-302
Number of pages6
DOIs
StatePublished - 2007
EventISM Workshops 2007 - 9th IEEE International Symposium on Multimedia - Workshops - Taichung, Taiwan, Province of China
Duration: Dec 10 2007Dec 12 2007

Publication series

NameProceedings ISM Workshops 2007 9th IEEE International Symposium on Multimedia - Workshops

Other

OtherISM Workshops 2007 - 9th IEEE International Symposium on Multimedia - Workshops
Country/TerritoryTaiwan, Province of China
CityTaichung
Period12/10/0712/12/07

ASJC Scopus subject areas

  • Computer Graphics and Computer-Aided Design
  • Software

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