Commenced in January 2007
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The Creative Unfolding of “Reduced Descriptive Structures” in Musical Cognition: Technical and Theoretical Insights Based on the OpenMusic and PWGL Long-Term Feedback

Authors: Jacopo Baboni Schilingi

Abstract:

We here describe the theoretical and philosophical understanding of a long term use and development of algorithmic computer-based tools applied to music composition. The findings of our research lead us to interrogate some specific processes and systems of communication engaged in the discovery of specific cultural artworks: artistic creation in the sono-musical domain. Our hypothesis is that the patterns of auditory learning cannot be only understood in terms of social transmission but would gain to be questioned in the way they rely on various ranges of acoustic stimuli modes of consciousness and how the different types of memories engaged in the percept-action expressive systems of our cultural communities also relies on these shadowy conscious entities we named “Reduced Descriptive Structures”.

Keywords: Algorithmic sonic computation, corrected and self-correcting learning patterns in acoustic perception, morphological derivations in sensorial patterns, social unconscious modes of communication.

Digital Object Identifier (DOI): doi.org/10.5281/zenodo.1474624

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[1] Herculano-Houzel, S. (2011). “Brains matter, bodies maybe not: the case for examining neuron numbers irrespective of body size”, in Annals of the Ney-York Academy of Science, 1225, pp. 191–199.
[2] Varela, F.J., Thompson, E., Rosch, E. (1992). The embodied mind: Cognitive science and human experience, MIT Press. p. 9
[3] Baboni-Schilingi, J., Voisin, F. (1999). Morphologie: Documentation OpenMusic, 3ème édition, Ircam, Paris.
[4] Mc. Adams, S., Deliège, I. (1995). La Musique et les sciences cognitives. Mardaga
[5] Giordano, B., McDonnell, J. & McAdams, S. (2010). “Hearing living symbols and nonliving icons: Category specificities in the cognitive processing of environmental sounds”, Brain and Cognition, 73, pp. 7-19.
[6] Giordano, B.L., Guastavino, C., Murphy, E., Ogg, M., Smith, B.K. & McAdams, S. (2011). “Comparison of methods for collecting and modeling dissimilarity data: Applications to complex sound stimuli”, Multivariate Behavioral Research, 46, pp. 779-811.
[7] Voisin, F. (2011). Dissemblance et espaces compositionnels, Conservatoire de Musique du Pays de Montbéliard, p.4.
[8] Deller, J. R., Proakis, J. G. and Hansen, J. H. L. (1999). Discrete-time processing of speech signals. Wiley-IEEE Press, New-York, p. 649-675.
[9] Myers, E. W. (1986). “An O(ND) Difference Algorithm and Its Variations”, Algorithmica, 1, Springer-Verlag New York Inc., pp. 251-266.
[10] Voisin, F. (2011). Dissemblance et espaces compositionnels, Conservatoire de Musique du Pays de Montbéliard, p.5.
[11] Chemillier, M. (2007). Les mathématiques naturelles. Paris : Odile Jacob.