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Metrical-accent Aware Vocal Onset Detection in Polyphonic Audio
KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID. (Sound and Music Computing)ORCID iD: 0000-0003-1679-6018
2017 (English)In: 18th International Society for Music Information Retrieval Conference, 2017Conference paper, Published paper (Refereed)
Abstract [en]

The goal of this study is the automatic detection of onsets of the singing voice in polyphonic audio recordings. Starting with a hypothesis that the knowledge of the current position in a metrical cycle (i.e. metrical accent) can improve the accuracy of vocal note onset detection, we propose a novel probabilistic model to jointly track beats and vocal note onsets. The proposed model extends a state of the art model for beat and meter tracking, in which a-priori probability of a note at a specific metrical accent interacts with the probability of observing a vocal note onset. We carry out an evaluation on a varied collection of multi-instrument datasets from two music traditions (English popular music and Turkish makam) with different types of metrical cycles and singing styles. Results confirm that the proposed model reasonably improves vocal note onset detection accuracy compared to a baseline model that does not take metrical position into account.

Place, publisher, year, edition, pages
2017.
National Category
Media and Communication Technology
Identifiers
URN: urn:nbn:se:kth:diva-215131OAI: oai:DiVA.org:kth-215131DiVA, id: diva2:1146589
Conference
18th International Society for Music Information Retrieval Conference, Suzhou, China
Note

QC 20171009

Available from: 2017-10-03 Created: 2017-10-03 Last updated: 2018-01-13Bibliographically approved

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fulltext(761 kB)5 downloads
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CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • 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
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