Music information retrieval using a GA-based relevance feedback

Seungmin Rho, Eenjun Hwang, Minkoo Kim

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

9 Citations (Scopus)

Abstract

Recently, there has been an increased interest in the query reformulation using relevance feedback with evolutionary techniques such as genetic algorithm for multimedia information retrieval. However, these techniques have still not been exploited widely in the field of music retrieval. In this paper, we propose a novel music retrieval scheme that incorporates user relevance feedback with genetic algorithm to improve retrieval performance and develop a prototype system based on it. Our system also provides interesting easy-to-use graphical user interfaces. For example, users can browse and play query results easily using markers in the music indicating those matched parts for the query. By performing various experiments, we show the effectiveness and efficiency of our proposed scheme.

Original languageEnglish
Title of host publicationProceedings - 2007 International Conference on Multimedia and Ubiquitous Engineering, MUE 2007
Pages739-744
Number of pages6
DOIs
Publication statusPublished - 2007
Event2007 International Conference on Multimedia and Ubiquitous Engineering, MUE 2007 - Seoul, Korea, Republic of
Duration: 2007 Apr 262007 Apr 28

Publication series

NameProceedings - 2007 International Conference on Multimedia and Ubiquitous Engineering, MUE 2007

Other

Other2007 International Conference on Multimedia and Ubiquitous Engineering, MUE 2007
CountryKorea, Republic of
CitySeoul
Period07/4/2607/4/28

ASJC Scopus subject areas

  • Software
  • Media Technology

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