Feature analysis and normalization approach for robust content-based music retrieval to encoded audio with different bit rates

Shuhei Hamawaki, Shintaro Funasawa, Jiro Katto, Hiromi Ishizaki, Keiichiro Hoashi, Yasuhiro Takishima

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

5 Citations (Scopus)

Abstract

In order to achieve highly accurate content-based music information retrieval (MIR), it is necessary to compensate the various bit rates of encoded songs which are stored in the music collection, since the bit rate differences are expected to apply a negative effect to content-based MIR results. In this paper, we examine how the bit rate differences affect MIR results, propose methods to normalize MFCC features extracted from encoded files with various bit rates, and show their effects to stabilize MIR results.

Original languageEnglish
Title of host publicationAdvances in Multimedia Modeling - 15th International Multimedia Modeling Conference, MMM 2009, Proceedings
Pages298-309
Number of pages12
DOIs
Publication statusPublished - 2009 Feb 5
Event15th International Multimedia Modeling Conference, MMM 2009 - Sophia-Antipolis, France
Duration: 2009 Jan 72009 Jan 9

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume5371 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Multimedia Modeling Conference, MMM 2009
CountryFrance
CitySophia-Antipolis
Period09/1/709/1/9

Keywords

  • Content-based MIR Normalization
  • Mel-Frequency Cepstral Coefficient (MFCC)

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Hamawaki, S., Funasawa, S., Katto, J., Ishizaki, H., Hoashi, K., & Takishima, Y. (2009). Feature analysis and normalization approach for robust content-based music retrieval to encoded audio with different bit rates. In Advances in Multimedia Modeling - 15th International Multimedia Modeling Conference, MMM 2009, Proceedings (pp. 298-309). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 5371 LNCS). https://doi.org/10.1007/978-3-540-92892-8_32