Artificial Grammar Learning of Melody Is Constrained by Melodic Inconsistency: Narmour's Principles Affect Melodic Learning
Author(s)
Rohrmeier, Martin Alois; Cross, Ian
DownloadRohrmeier-2013-Artificial Grammar L.pdf (613.1Kb)
PUBLISHER_CC
Publisher with Creative Commons License
Creative Commons Attribution
Terms of use
Metadata
Show full item recordAbstract
Considerable evidence suggests that people acquire artificial grammars incidentally and implicitly, an indispensable capacity for the acquisition of music or language. However, less research has been devoted to exploring constraints affecting incidental learning. Within the domain of music, the extent to which Narmour's (1990) melodic principles affect implicit learning of melodic structure was experimentally explored. Extending previous research (Rohrmeier, Rebuschat & Cross, 2011), the identical finite-state grammar is employed having terminals (the alphabet) manipulated so that melodies generated systematically violated Narmour's principles. Results indicate that Narmour-inconsistent melodic materials impede implicit learning. This further constitutes a case in which artificial grammar learning is affected by prior knowledge or processing constraints.
Date issued
2013-07Department
Massachusetts Institute of Technology. Department of Linguistics and PhilosophyJournal
PLoS ONE
Publisher
Public Library of Science
Citation
Rohrmeier, Martin, and Ian Cross. “Artificial Grammar Learning of Melody Is Constrained by Melodic Inconsistency: Narmour s Principles Affect Melodic Learning.” Edited by Joel Snyder. PLoS ONE 8, no. 7 (July 9, 2013): e66174.
Version: Final published version
ISSN
1932-6203