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Which melodic universals emerge from repeated signaling games?: A Note on Lumaca and Baggio (2017)

MPG-Autoren
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Ravignani,  Andrea
Language and Cognition Department, MPI for Psycholinguistics, Max Planck Society;
Vrije Universiteit Brussel;
Sealcentre Pieterburen;

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Zitation

Ravignani, A., & Verhoef, T. (2018). Which melodic universals emerge from repeated signaling games?: A Note on Lumaca and Baggio (2017). Artificial Life, 24(2), 149-153. doi:10.1162/ARTL_a_00259.


Zitierlink: https://hdl.handle.net/11858/00-001M-0000-002E-77A8-F
Zusammenfassung
Music is a peculiar human behavior, yet we still know little as to why and how music emerged. For centuries, the study of music has been the sole prerogative of the humanities. Lately, however, music is being increasingly investigated by psychologists, neuroscientists, biologists, and computer scientists. One approach to studying the origins of music is to empirically test hypotheses about the mechanisms behind this structured behavior. Recent lab experiments show how musical rhythm and melody can emerge via the process of cultural transmission. In particular, Lumaca and Baggio (2017) tested the emergence of a sound system at the boundary between music and language. In this study, participants were given random pairs of signal-meanings; when participants negotiated their meaning and played a “ game of telephone ” with them, these pairs became more structured and systematic. Over time, the small biases introduced in each artificial transmission step accumulated, displaying quantitative trends, including the emergence, over the course of artificial human generations, of features resembling properties of language and music. In this Note, we highlight the importance of Lumaca and Baggio ʼ s experiment, place it in the broader literature on the evolution of language and music, and suggest refinements for future experiments. We conclude that, while psychological evidence for the emergence of proto-musical features is accumulating, complementary work is needed: Mathematical modeling and computer simulations should be used to test the internal consistency of experimentally generated hypotheses and to make new predictions.