Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Modelling Perception of Speed in Music Audio
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics.ORCID iD: 0000-0002-4957-2128
KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Music Acoustics.ORCID iD: 0000-0003-2926-6518
2013 (English)In: Proceedings of the Sound and Music Computing Conference 2013, 2013, 735-741 p.Conference paper, Published paper (Refereed)
Abstract [en]

One of the major parameters in music is the overall speed of a musical performance. Speed is often associated with tempo, but other factors such as note density (onsets per second) seem to be important as well. In this study, a computational model of speed in music audio has been developed using a custom set of rhythmic features. The original audio is first separated into a harmonic part and a percussive part and onsets are extracted separately from the different layers. The characteristics of each onset are determined based on frequency content as well as perceptual salience using a clustering approach. Using these separated onsets a set of eight features including a tempo estimation are defined which are specifically designed for modelling perceived speed. In a previous study 20 listeners rated the speed of 100 ringtones consisting mainly of popular songs, which had been converted from MIDI to audio. The ratings were used in linear regression and PLS regression in order to evaluate the validity of the model as well as to find appropriate features. The computed audio features were able to explain about 90 % of the variability in listener ratings.

Place, publisher, year, edition, pages
2013. 735-741 p.
National Category
Computer Science Language Technology (Computational Linguistics)
Identifiers
URN: urn:nbn:se:kth:diva-137404ISBN: 9789175018317 (print)OAI: oai:DiVA.org:kth-137404DiVA: diva2:678904
Conference
SMC Sound and Music Computing Conference 2013; Stockholm, Sweden, 30 July-3 August, 2013
Note

tmh_import_13_12_13, tmh_id_3878

QC 20140213

Available from: 2013-12-13 Created: 2013-12-13 Last updated: 2014-02-13Bibliographically approved

Open Access in DiVA

No full text

Other links

Proceedings at Sound and Music Computing

Authority records BETA

Friberg, Anders

Search in DiVA

By author/editor
Elowsson, AndersFriberg, Anders
By organisation
Music Acoustics
Computer ScienceLanguage Technology (Computational Linguistics)

Search outside of DiVA

GoogleGoogle Scholar

isbn
urn-nbn

Altmetric score

isbn
urn-nbn
Total: 58 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf