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Assigning a confidence threshold on automatic beat annotation in large datasets
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2012 (English)In: Proceedings of ISMIR - International Conference on Music Information Retrieval, 2012, 157-162 p.Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we establish a threshold for perceptually acceptable beat tracking based on the mutual agreement of a committee of beat trackers. In the first step we use an existing annotated dataset to show that mutual agreement can be used to select one committee member as the most reliable beat tracker for a song. Then we conduct a listening test using a subset of the Million Song Dataset to establish a threshold which results in acceptable quality of the chosen beat output. For both datasets, we obtain a percent age of trackable music of about 73%, and we investigate which data tags are related to acceptable and problematic beat tracking. The results indicate that current datasets are biased towards genres which tend to be easy for beat tracking. The proposed methods provide a means to automatically obtain a confidence value for beat tracking in non-annotated data and to choose between a number of beat tracker outputs.

Place, publisher, year, edition, pages
2012. 157-162 p.
National Category
Media and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-193778OAI: oai:DiVA.org:kth-193778DiVA: diva2:1033966
Conference
13th International Society for Music Information Retrieval Conference, 08/10/2012, Porto, Portugal
Note

QC 20161012

Available from: 2016-10-10 Created: 2016-10-10 Last updated: 2016-10-12Bibliographically approved

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Holzapfel, Andre
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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