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A CASE STUDY OF DEEP ENCULTURATION AND SENSORIMOTOR SYNCHRONIZATION TO REAL MUSIC
Royal College of Music in Stockholm, Department of Folk Music.ORCID iD: 0000-0003-0646-5426
Royal College of Music in Stockholm, Department of Jazz.ORCID iD: 0000-0002-8623-8591
KTH, Skolan för elektroteknik och datavetenskap (EECS), Människocentrerad teknologi, Medieteknik och interaktionsdesign, MID. (Sound and Music Computing).
KTH, Skolan för elektroteknik och datavetenskap (EECS), Människocentrerad teknologi, Medieteknik och interaktionsdesign, MID. (Sound and Music Computing).ORCID iD: 0000-0003-1679-6018
2021 (English)Conference paper, Published paper (Refereed)
Abstract [en]

Synchronization of movement to music is a behavioural capacity that separates humans from most other species. Whereas such movements have been studied using a wide range of methods, only few studies have investigated synchronisation to real music stimuli in a cross-culturally comparative setting. The present study employs beat tracking evaluation metrics and accent histograms to analyze the differences in the ways participants from two cultural groups synchronize their tapping with either familiar or unfamiliar music stimuli. Instead of choosing two apparently remote cultural groups, we selected two groups of musicians that share cultural backgrounds, but that differ regarding the music style they specialize in. The employed method to record tapping responses in audio format facilitates a fine-grained analysis of metrical accents that emerge from the responses. The identified differences between groups are related to the metrical structures inherent to the two musical styles, such as non-isochronicity of the beat, and differences between the groups document the influence of the deep enculturation of participants to their style of expertise. Besides these findings, our study sheds light on a conceptual weakness of a common beat tracking evaluation metric, when applied to human tapping instead of machine generated beat estimations.

Place, publisher, year, edition, pages
2021.
National Category
Music Other Computer and Information Science
Identifiers
URN: urn:nbn:se:kmh:diva-4238OAI: oai:DiVA.org:kmh-4238DiVA, id: diva2:1601509
Conference
ISMIR - International Society for Music Information Retrieval Conference
Funder
Swedish Research Council, 2019-03694Marianne and Marcus Wallenberg Foundation, MMW 2020.0102Available from: 2021-10-08 Created: 2021-10-08 Last updated: 2021-10-08

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Misgeld, OlofGulz, TorbjörnHolzapfel, Andre
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CiteExportLink to record
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Citation style
  • apa
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