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Computational Modeling of Musical Enculturation: An Investigation of Multicultural Music Learning Using Self-Organizing Maps

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dc.contributor.advisor Chandlee, Jane
dc.contributor.advisor Boltz, Marilyn
dc.contributor.author Pazdera, Jesse
dc.date.accessioned 2016-05-26T13:38:14Z
dc.date.available 2016-05-26T13:38:14Z
dc.date.issued 2016
dc.identifier.uri http://hdl.handle.net/10066/18375
dc.description.abstract Past research has shown that children are able to implicitly learn the underlying melodic structure of their native culture's musical system, even without formal musical training. Although implicit musical learning has been well studied, little is known about non-Western and multicultural musical enculturation. The present study addressed these issues though three experiments using self-organizing maps (SOMs), a type of neural model, to simulate implicit musical learning. Experiment 1 used SOMs to simulate Western, Chinese, and Hindustani musical enculturation, each learned independently from one another. Experiment 2 simulated a child growing up in a multicultural context, to investigate whether they might learn the structure of multiple native systems. Experiment 3 simulated an adult encountering an unfamiliar culture, to examine whether adults – not only children – may implicitly acquire the syntax of new musical systems. Results generally supported the plausibility of successful multicultural learning, with the caveat that certain systems disrupted the learning of others. Our findings led to further discussion of cross-cultural similarities between musical systems and the implications of these connections.
dc.description.sponsorship Haverford College. Department of Computer Science
dc.language.iso eng
dc.rights.uri http://creativecommons.org/licenses/by-nc/4.0/
dc.title Computational Modeling of Musical Enculturation: An Investigation of Multicultural Music Learning Using Self-Organizing Maps
dc.type Thesis
dc.rights.access Open Access


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