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  1. Implicit Learning and Acquisition of Music.Martin Rohrmeier & Patrick Rebuschat - 2012 - Topics in Cognitive Science 4 (4):525-553.
    Implicit learning is a core process for the acquisition of a complex, rule‐based environment from mere interaction, such as motor action, skill acquisition, or language. A body of evidence suggests that implicit knowledge governs music acquisition and perception in nonmusicians and musicians, and that both expert and nonexpert participants acquire complex melodic, harmonic, and other features from mere exposure. While current findings and computational modeling largely support the learning of chunks, some results indicate learning of more complex structures. Despite the (...)
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  • Musicians’ Online Performance during Auditory and Visual Statistical Learning Tasks.Pragati R. Mandikal Vasuki, Mridula Sharma, Ronny K. Ibrahim & Joanne Arciuli - 2017 - Frontiers in Human Neuroscience 11.
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  • Predictive uncertainty in auditory sequence processing.Niels Chr Hansen & Marcus T. Pearce - 2014 - Frontiers in Psychology 5:88945.
    Previous studies of auditory expectation have focused on the expectedness perceived by listeners retrospectively in response to events. In contrast, this research examines predictive uncertainty —a property of listeners' prospective state of expectation prior to the onset of an event. We examine the information-theoretic concept of Shannon entropy as a model of predictive uncertainty in music cognition. This is motivated by the Statistical Learning Hypothesis, which proposes that schematic expectations reflect probabilistic relationships between sensory events learned implicitly through exposure. Using (...)
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  • Expectation adaptation for rare cadences in music: Item order matters in repetition priming.Aditya Chander & Richard N. Aslin - 2023 - Cognition 240 (C):105601.
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  • Generality and specificity in the effects of musical expertise on perception and cognition.Daniel Carey, Stuart Rosen, Saloni Krishnan, Marcus T. Pearce, Alex Shepherd, Jennifer Aydelott & Frederic Dick - 2015 - Cognition 137 (C):81-105.
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  • Music Perception Abilities and Ambiguous Word Learning: Is There Cross-Domain Transfer in Nonmusicians?Eline A. Smit, Andrew J. Milne & Paola Escudero - 2022 - Frontiers in Psychology 13:801263.
    Perception of music and speech is based on similar auditory skills, and it is often suggested that those with enhanced music perception skills may perceive and learn novel words more easily. The current study tested whether music perception abilities are associated with novel word learning in an ambiguous learning scenario. Using a cross-situational word learning (CSWL) task, nonmusician adults were exposed to word-object pairings between eight novel words and visual referents. Novel words were either non-minimal pairs differing in all sounds (...)
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  • Incidental Learning of Melodic Structure of North Indian Music.Martin Rohrmeier & Richard Widdess - 2017 - Cognitive Science 41 (5):1299-1327.
    Musical knowledge is largely implicit. It is acquired without awareness of its complex rules, through interaction with a large number of samples during musical enculturation. Whereas several studies explored implicit learning of mostly abstract and less ecologically valid features of Western music, very little work has been done with respect to ecologically valid stimuli as well as non-Western music. The present study investigated implicit learning of modal melodic features in North Indian classical music in a realistic and ecologically valid way. (...)
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  • New music system reveals spectral contribution to statistical learning.Psyche Loui - 2022 - Cognition 224 (C):105071.
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  • Redefining “Learning” in Statistical Learning: What Does an Online Measure Reveal About the Assimilation of Visual Regularities?Noam Siegelman, Louisa Bogaerts, Ofer Kronenfeld & Ram Frost - 2018 - Cognitive Science 42 (S3):692-727.
    From a theoretical perspective, most discussions of statistical learning have focused on the possible “statistical” properties that are the object of learning. Much less attention has been given to defining what “learning” is in the context of “statistical learning.” One major difficulty is that SL research has been monitoring participants’ performance in laboratory settings with a strikingly narrow set of tasks, where learning is typically assessed offline, through a set of two-alternative-forced-choice questions, which follow a brief visual or auditory familiarization (...)
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