Can Ubimus Technologies affect our Musicality?

Leandro Costalonga; Marcelo Pimenta; Marcelo Wanderley

doi:10.35699/2317-6377.2020.25941

Authors

Leandro Costalonga Federal University of Espírito Santo, Brazil https://orcid.org/0000-0002-0252-9624
Marcelo Pimenta Federal University of Rio Grande do Sul, Brazil https://orcid.org/0000-0002-4712-089X
Marcelo Wanderley McGill University, Canada https://orcid.org/0000-0002-9169-4313

DOI:

https://doi.org/10.35699/2317-6377.2020.25941

Keywords:

Cognitive Offloading, Musicality, Ubimus technology

Abstract

Recent works recognize musicality is based on and constrained by our cognitive and biological system. Taking in account a concept from cognitive science - cognitive offloading - as a principle for technology-supported musical activities, in this paper we discuss some principles (guidelines) to be taken into account when designing, developing and evaluating computer music technologies, especially those related to ubimus. We think that Ubimus technology can shape the way we think about music and have a positive (or negative) influence on our musicality.

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Author Biographies

Leandro Costalonga, Federal University of Espírito Santo, Brazil

Leandro Costalonga has a Computer Science Degree with Masters (UFRGS/Brazil) and PhD (University of Plymouth/UK) in Computer Music. Associate professor at the Federal University of Espírito Santo (UFES/Brazil) where teaches on undergraduate programs in Computer Science and Computer Engineering and Graduate Program in Arts. Head of the NESCoM Research Group that carries on Computer Music related research, especially on Ubiquitous Music. Besides Computer Music, other research interest includes Human-Computer Interaction, Programming Languages and Artificial Intelligence.

Marcelo Pimenta, Federal University of Rio Grande do Sul, Brazil

Marcelo S. Pimenta is Full Professor at Institute of Informatics (INF), Federal University of Rio Grande do Sul (UFRGS), Brazil. He received his PhD in Informatique at Université Toulouse 1, France in 1997. Since 1998, he is member of a multidisciplinary research group at UFRGS working with topics in Human-Computer Interaction, Software Engineering, and Computer Music with emphasis in the integration of these areas. He is head of Laboratório de Computação Musical (LCM), the INF-UFRGS Computer Music Laboratory and founder of the Ubiquitous Music Group.

Marcelo Wanderley, McGill University, Canada

Marcelo M. Wanderley is Full Professor of Music Technology at McGill University (Montreal, Canada) and member of Computer Music Journal’s editorial advisory board. He co-edited the electronic book “Trends in Gestural Control of Music”, 2000, the book “New Directions in Music and Human-Computer Interaction“, 2019, and co-authored the textbook “New Digital Musical Instruments: Control and Interaction Beyond the Keyboard”, 2006. He is a senior member of the ACM and the IEEE.

References

Baily, J.. 1985. Music structure and human movement. In Cross, Ian, West, Robert, and Howell, Peter, editors, Musical structure and cognition, chapter 10, 237–58. Academic Press, London.

Barr, Nathaniel, Pennycook, Gordon, Stolz, Jennifer A., and Fugelsang, Jonathan A.. 2015. The brain in your pocket: Evidence that Smartphones are used to supplant thinking. Computers in Human Behavior, 48:473– 480.

Bean, K. L.. 1939. Reading music instead of spelling it. Journal of Musicology, 1–5.

Bech‐Hansen, Mikkel. 2013. Musical Instrument Interfaces. A Peer‐Reviewed Journal About, 1(1):10.

Brown, Steven. 2011. Evolutionary Models of Music: From Sexual Selection to Group Selection. In Thompson, François TonneauNicholas S., editor, Perspectives in Ethology, 231–281. Springer, Boston, MA, Boston, MA.

Buccino, Giovanni, Binkofski, Ferdinand, and Riggio, Lucia. 2004. The mirror neuron system and action recog‐ nition. Brain and Language, 89(2):370–376.

Byrne, R W and Russon, A E. 1998. Learning by imitation: a hierarchical approach. The Behavioral and brain sciences, 21(5):667–84; discussion 684–721.

Carr, Nicholas. 2010. The Shallows: what the internet is doing to our brains. W.W. Norton & Company, New York, New York, USA, 1 edition.

Clayton, Russell B., Leshner, Glenn, and Almond, Anthony. 2015. The Extended iSelf: The Impact of iPhone Sep‐ aration on Cognition, Emotion, and Physiology. Journal of Computer‐Mediated Communication, 20(2):119– 135.

De Lima, Maria Helena, Keller, Damián, Flores, Luciano Vargas, and Ferreira, Edemilson. 2017. Ubiquitous music research: Everyday musical phenomena and their multidisciplinary implications for creativity and education. Journal of Music, Technology & Education, 10(1):73–92.

Dissanayake, Ellen. 2008. If music is the food of love, what about survival and reproductive success? Musicae Scientiae, 12(1_suppl):169–195.

Dogantan‐Dack, Mine. 2006. The body behind music: Precedents and prospects. Psychology of Music, 34(4):449–464.

Fitch, W. Tecumseh. 2006. The biology and evolution of music: A comparative perspective. Cognition, 100(1):173–215.

Fitch, W. Tecumseh. 2013. Rhythmic cognition in humans and animals: distinguishing meter and pulse per‐ ception. Frontiers in Systems Neuroscience, 7:68.

Fitch, W. T.. 2015. Four principles of bio‐musicology. Philosophical Transactions of the Royal Society B: Bio‐ logical Sciences, 370(1664):20140091–20140091.

Fraisse, P.. 1982. Rhythm and tempo. The psychology of music, 2:149–180.

Friberg, A. and Sundberg, J.. 1999. Does music performance allude to locomotion? A model of final ritardandi derived from measurements of stopping runners. Journal of the Acoustical Society of America, 105(3):1469– 1484.

Gabrielsson, A.. 2003. Music performance research at the millennium. Psychology of Music, 31(3):221. Hallam, Susan, Cross, Ian, and Thaut, Michael. 2005. The Oxford handbook of music psychology. Oxford University Press, Oxford, UK, 1 edition.

Hartanto, Andree and Yang, Hwajin. 2016. Is the smartphone a smart choice? The effect of smartphone separation on executive functions. Computers in Human Behavior, 64:329–336.

Honing, H. 2003. The final ritard: On music, motion, and kinematic models. Computer Music Journal, 27(3):66–72.

Honing, Henkjan. 2012. Without it no music: beat induction as a fundamental musical trait. Annals of the New York Academy of Sciences, 1252(1):85–91.

Honing, Henkjan. 2018. The origins of musicality. The MIT Press, Cambridge, Massachusetts, USA, 1 edition. Honing, Henkjan and Ploeger, Annemie. 2012. Cognition and the Evolution of Music: Pitfalls and Prospects. Topics in Cognitive Science, 4(4):513–524.

Kahneman, Daniel. 2011. Thinking, fast and slow. American Psychological Association.

Keller, Damián and Lazzarini, Victor. 2017. Ecologically grounded creative practices in ubiquitous music. Organised Sound, 22(SI1):61–72.

Keller, Damián, Lazzarini, Victor, and Pimenta, Marcelo S., editors. 2014. Ubiquitous Music. Computational Music Science. Springer International Publishing, Cham.

Knuf, Lothar, Aschersleben, Gisa, and Prinz, Wolfgang. 2001. An analysis of ideomotor action. Journal of Experimental Psychology: General, 130(4):779–798.

Leman, Marc. 2008. Embodied music cognition and mediation technology. MIT Press, Cambridge, Massachusetts.

Magnusson, Thor and Mendieta, Enrike Hurtado. 2007. The acoustic, the digital and the body. In Proceedings of the 7th international conference on New interfaces for musical expression ‐ NIME ’07, 94, New York, New York, USA. ACM Press.

Malloch, Joseph and Wanderley, Marcelo M. 2017. Embodied cognition and digital musical instruments: de‐ sign and performance. In The Routledge companion to embodied music interaction, 438–447. Routledge.

Manchester, Ralph A.. 2006. Musical instrument ergonomics. Medical Problems of Performing Artists, 21(4):157–159.

Mann, Steve and Steve. 2007. Natural interfaces for musical expression. In Proceedings of the 7th international conference on New interfaces for musical expression ‐ NIME ’07, 118, New York, New York, USA. ACM Press.

McLuhan, Marshall and Lapham, Lewis H.. 1994. Understanding media : the extensions of man. MIT Press, Cambridge, USA.

Merker, B., Morley, I., and Zuidema, W.. 2015. Five fundamental constraints on theories of the origins of music. Philosophical Transactions of the Royal Society B: Biological Sciences, 370(1664):20140095–20140095.

Merker, Bjorn H., Madison, Guy S., and Eckerdal, Patricia. 2009. On the role and origin of isochrony in human rhythmic entrainment. Cortex, 45(1):4–17.

Miletto, Evandro Manara, Flores, Luciano Vargas, Pimenta, Marcelo Soares, Rutily, Jérôme, and Santagada, Leonardo. 2007. Interfaces for Musical Activities and Interfaces for Musicians Are Not the Same: The Case for Codes, a Web‐Based Environment for Cooperative Music Prototyping. In Proceedings of the 9th In‐ ternational Conference on Multimodal Interfaces, ICMI ’07, 201–207, New York, NY, USA. Association for Computing Machinery.

Miranda, Eduardo Reck and Wanderley, Marcelo M. 2006. New digital musical instruments: control and interaction beyond the keyboard, volume 21. AR Editions, Inc.

Oikkonen, Jaana, Onkamo, Päivi, Järvelä, Irma, and Kanduri, Chakravarthi. 2016. Convergent evidence for the molecular basis of musical traits. Scientific Reports, 6(1):39707.

Patel, Aniruddh D.. 2008. Music, language, and the brain. Oxford University Press, New York, NY.

Preece, Jenny, Rogers, Yvonne, and Sharp, Helen. 2015. Interaction design : beyond human‐computer interaction. Wiley, Chichester, UK., 4 edition.

Repp, B. H.. 1991. Some cognitive and perceptual aspects of speech and music. In Music, Language, Speech and Brain, 257–268. Macmillan Education UK, London.

Risko, Evan F. and Gilbert, Sam J.. 2016. Cognitive Offloading. Trends in Cognitive Sciences, 20(9):676–688.

Särkämö, Teppo, Altenmüller, Eckart, Rodríguez‐Fornells, Antoni, and Peretz, Isabelle. 2016. Editorial: Music, Brain, and Rehabilitation: Emerging Therapeutic Applications and Potential Neural Mechanisms. Frontiers in Human Neuroscience, 10:103.

Savage, Patrick E, Brown, Steven, Sakai, Emi, and Currie, Thomas E. 2015. Statistical universals reveal the structures and functions of human music. Proceedings of the National Academy of Sciences of the United States of America, 112(29):8987–92.

Shan, G. B. and Visentin, P.. 2003. A quantitative three‐dimensional analysis of arm kinematics in violin per‐ formance. Medical Problems of Performing Artists, 18(1):3–10.

Sparrow, Betsy, Liu, Jenny, and Wegner, Daniel M. 2011. Google effects on memory: cognitive consequences of having information at our fingertips. Science (New York, N.Y.), 333(6043):776–8.

Stanovich, Keith E.. 2004. The robot’s rebellion : finding meaning in the age of Darwin. University of Chicago Press.

Taylor, Shelley E. 1981. The interface of cognitive and social psychology. Cognition, social behavior, and the environment, 1:189–211.

ten Cate, Carel, Spierings, Michelle, Hubert, Jeroen, and Honing, Henkjan. 2016. Can Birds Perceive Rhythmic Patterns? A Review and Experiments on a Songbird and a Parrot Species. Frontiers in Psychology, 7:730.

Todd, N. P. M.. 1992. The dynamics of dynamics ‐ a model of musical expression. Journal of the Acoustical Society of America, 91(6):3540–3550.

Trehub, Sandra E, Becker, Judith, and Morley, Iain. 2015. Cross‐cultural perspectives on music and musicality. Philosophical transactions of the Royal Society of London. Series B, Biological sciences, 370(1664):20140096.

Turchet, Luca and Barthet, Mathieu. 2017. An Internet of Musical Things architecture for performers‐audience tactile interactions. In Proceedings of the Digital Music Research Network Workshop.

Turchet, Luca, Fischione, Carlo, Essl, Georg, Keller, Damian, and Barthet, Mathieu. 2018. Internet of Musical Things: Vision and Challenges. IEEE Access, 6:61994–62017.

Wanderley, Marcelo. 2002. Quantitative Analysis of Non‐Obvious Performer Gestures. In Wachsmuth, I. and Sowa, T., editors, Gesture and Sign Language in Human‐Computer Interaction, 241–53. Springer Verlag, Heidelberg.

Wanderley, Marcelo M, Vines, Bradley, Middleton, Neil, McKay, Cory, and Hatch, Wesley. 2005. The Musical Significance of Clarinetists’ Ancillary Gestures: An Exploration of the Field. Journal of New Music Research, 34(1):97–113.

Weiser, Mark. 1991. The Computer for the 21 st Century. Scientific American, 265:94–105.

Winkler, István, Háden, Gábor P, Ladinig, Olivia, Sziller, István, and Honing, Henkjan. 2009. Newborn infants detect the beat in music. Proceedings of the National Academy of Sciences of the United States of America, 106(7):2468–71.

Can Ubimus Technologies affect our Musicality?

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DOI:

Keywords:

Abstract

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Author Biographies

Leandro Costalonga, Federal University of Espírito Santo, Brazil

Marcelo Pimenta, Federal University of Rio Grande do Sul, Brazil

Marcelo Wanderley, McGill University, Canada

References

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