Effects of audio compression on chord recognition

Aiko Uemura, Kazumasa Ishikura, Jiro Katto

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

1 Citation (Scopus)

Abstract

Feature analysis of audio compression is necessary to achieve high accuracy in musical content recognition and content-based music information retrieval (MIR). Bit rate differences are expected to adversely affect musical content analysis and content-based MIR results because the frequency response might be changed by the encoding. In this paper, we specifically examine its effect on the chroma vector, which is a commonly used feature vector for music signal processing. We analyze sound qualities extracted from encoded music files with different bit rates and compare them with the chroma features of original songs obtained using datasets for chord recognition.

Original languageEnglish
Title of host publicationMultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings
Pages345-352
Number of pages8
EditionPART 2
DOIs
Publication statusPublished - 2014 Feb 7
Event20th Anniversary International Conference on MultiMedia Modeling, MMM 2014 - Dublin, Ireland
Duration: 2014 Jan 62014 Jan 10

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
NumberPART 2
Volume8326 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference20th Anniversary International Conference on MultiMedia Modeling, MMM 2014
CountryIreland
CityDublin
Period14/1/614/1/10

Keywords

  • audio compression
  • chord recognition
  • chroma vector

ASJC Scopus subject areas

  • Theoretical Computer Science
  • Computer Science(all)

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  • Cite this

    Uemura, A., Ishikura, K., & Katto, J. (2014). Effects of audio compression on chord recognition. In MultiMedia Modeling - 20th Anniversary International Conference, MMM 2014, Proceedings (PART 2 ed., pp. 345-352). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 8326 LNCS, No. PART 2). https://doi.org/10.1007/978-3-319-04117-9_34