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  1. How Do Artificial Neural Networks Classify Musical Triads? A Case Study in Eluding Bonini's Paradox.Arturo Perez, Helen L. Ma, Stephanie Zawaduk & Michael R. W. Dawson - 2023 - Cognitive Science 47 (1):e13233.
    How might artificial neural networks (ANNs) inform cognitive science? Often cognitive scientists use ANNs but do not examine their internal structures. In this paper, we use ANNs to explore how cognition might represent musical properties. We train ANNs to classify musical chords, and we interpret network structure to determine what representations ANNs discover and use. We find connection weights between input units and hidden units can be described using Fourier phase spaces, a representation studied in musical set theory. We find (...)
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  • 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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