SYMBOLIC MUSICAL RESYNTHESIS AS AN EKPHRASTIC COMPOSITIONAL PRACTICE USING COMPUTATIONAL METHODS
DOI:
https://doi.org/10.55877/cc.vol22.443Keywords:
computer-assisted composition, symbolic resynthesis, constraint algorithms, Markov chainsAbstract
In my artistic work, I explore the affordances of computational methods from the discipline of artificial intelligence for music composition. Grounded in philosophical perspectives that revolve around the notions of trans- and post-humanism and cybernetics, I understand the mediating role of computers in music composition as having the potential to expand a composer’s creative process by providing him with novel ways of exploring relationships between musical material and structure. Under this premise, music composition becomes a process that occurs through the assemblage between human actors and technological artifacts, and this association should result in new, interesting, and valuable artistic works. In this text, I will discuss a personal compositional practice that I understand as ekphrastic, based on the notion of symbolic resynthesis of musical symbolic information employing computational methods, as means for composing an original piece in response to the madrigal “Io Mi Son Giovinetta” by Claudio Monteverdi.
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References
Boden, M. A. (2003). The creative mind: Myths and mechanisms. In: The Creative Mind: Myths and Mechanisms: Second Edition.
Bostrom, N. (2005). A History of Transhumanist Thought. Journal of Evolution and Technology, 1(April), 1–25.
Bown, O. (2021). Sociocultural and Design Perspectives on AI-Based Music Production: Why Do We Make Music and What Changes if AI Makes It for Us? In: E. R. Miranda (ed.). Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity. Springer International Publishing, pp. 1–20. Available: https://doi.org/10.1007/978-3-030-72116-9_1
Brendt, J. (2002). El Jazz: de Nueva Orleans a los años ochenta. Fondo de Cultura Económica.
Bruhn, S. (2001). A Concert of Paintings: “Musical Ekphrasis” in the Twentieth Century. Poetics Today, 22(3), 551–605. Available: https://doi.org/10.1215/03335372-22-3-551
Clark, A. (2004). Natural-Born Cyborgs: Minds, Technologies, and the Future of Human Intelligence (Vol. 29, Issue 3). Oxford University Press. Available: https://doi.org/10.2307/3654679
Clark, A. (2008). Supersizing the Mind: Embodiment, Action, and Cognitive Extension. Oxford University Press.
Clark, A. (2017). Where brain, body, and world collide. The Brain, 127(2), 257–280. Available: https://doi.org/10.4324/9781351305204-11
Clark, A., & Chalmers, D. J. (1998). The Extended Mind. Analysis, 58(1), 7–19.
Clynes, M., & Kline, N. (1960). Cyborgs and space. Astronautics, September, 26–27, 74–75.
Colton, S., & Wiggins, G. A. (2012). Computational creativity: The final frontier? Frontiers in Artificial Intelligence and Applications, 242, 21–26. Available: https://doi.org/10.3233/978-1-61499-098-7-21
Davidson, M. (1983). Ekphrasis and the Postmodern Painter Poem. The Journal of Aesthetics and Art Criticism, 42(1), 69. Available: https://doi.org/10.2307/429948
Essl, K. (2007). Algorithmic composition. In: The Cambridge Companion to Electronic Music. Cambridge University Press, pp. 107–125. Available: https://doi.org/10.1017/CCOL9780521868617.008
Fernández, J. D., & Vico, F. (2013). Ai methods in algorithmic composition: A comprehensive survey. Journal of Artificial Intelligence Research, 48, 513–582. Available:https://doi.org/10.1613/jair.3908
Goehr, L. (2010). How to Do More with Words. Two Views of (Musical) Ekphrasis. British Journal of Aesthetics, 50(4), 389–410.
Hayles, N. (2016). Cognitive assemblages: Technical agency and human interactions. Critical Inquiry, 43(1), 32–55. Available: https://doi.org/10.1086/688293
Hayles, N. K. (1999). How we became posthuman: virtual bodies in cybernetics, literature, and informatics. University of Chicago Press.
Heffernan, J. A. W. (1991). Ekphrasis and Representation. New Literary History, 22(2), 297–316. Available: https://doi.org/10.2307/469040
Hiller, Jr., L. A., & Isaacson, L. M. (2019). Musical Composition with a High-Speed Digital Computer. Machine Models of Music, Vol. 6, Issue 3, pp. 154–160. OxfordUniversity Press. Available: https://doi.org/10.7551/mitpress/4360.003.0004
Krieger, M. (1967). Ekphrasis and the still movement of poetry; or, Laokoön revisited. The Poet as Critic, 3, 26.
Kurzweil, R. (2000). The age of spiritual machines: When computers exceed human intelligence. Penguin.
Latour, B. (1994a). On technical mediation. Common Knowledge, 3(2).
Latour, B. (1994b). On Technical Mediation – Philosophy, Sociology, Genealogy. Common Knowledge, 3(2), 29–64.
Laurson, M. (1996). PatchWork: a visual programming language and some musical applications. 313.
Lui, Y. (2006). Modeling Music as Markov Chains: Composer Identification. Stanford, 1–6.
McClary, S. K. (1976). The transition from modal to tonal organization in the works of Claudio Monteverdi. Harvard University.
Miller, R. (1996). Modal Jazz, Composition and Harmony. advance music GmbH, pp. 1–288.
Moffat, D. C., & Kelly, M. (2006). An investigation into people’s bias against computational creativity in music composition. Proceedings of the International Joint Workshop on Computational Creativity.
Moravec, H. (1988). Mind children: the future of robot and human intelligence. Harvard University Press.
Rutz, H. H. (2021). Human-Machine Simultaneity in the Compositional Process. Available: https://doi.org/10.1007/978-3-030-72116-9_2
Ryle, G. (1949). The concept of mind. Hutchinson.
Sandred, O. (2017). The musical fundamentals of computer assisted composition. Audiospective Media.
Sandred, Ö. (2009). Approaches to Using Rules as a Composition Method. Contemporary Music Review, 28(2), 149–165. Available:https://doi.org/10.1080/07494460903322430
Sandred, Ö. (2021). Constraint-Solving Systems in Music Creation. In: E. R. Miranda (ed.). Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity. Springer International Publishing, pp. 327–344. Available: https://doi.org/10.1007/978-3-030-72116-9_12
Seyr, H., & Muskulus, M. (2019). Decision Support Models for Operations and Maintenance for Offshore Wind Farms: A Review. Applied Sciences, 9. Available:https://doi.org/10.3390/app9020278
Turing, A. (1950). Computing machinery and intelligence. Mind – A Quarterly Review, 433–460.
Volchenkov, D., & Dawin, J. R. (2012). Musical Markov Chains. International Journal of Modern Physics: Conference Series, 16, 116–135. Available: https://doi.org/10.1142/s2010194512007829
Wang, C. I., Hsu, J., & Dubnov, S. (2016). Machine improvisation with Variable Markov Oracle: Toward guided and structured improvisation. Computers in Entertainment, 14(3). Available: https://doi.org/10.1145/2905371
Webb, R. (2013). Ekphrasis, imagination and persuasion in ancient rhetorical theory and practice. In: Ekphrasis, Imagination and Persuasion in Ancient Rhetorical Theory and Practice. Taylor & Francis Group. Available: https://doi.org/10.33137/aestimatio.v5i0.25883
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