Music Production Based on Brainwave and Acoustic Theory
DOI:
https://doi.org/10.54097/3k720216Keywords:
Brainwave; music; electroencephalograph (EEG); psychology.Abstract
The fusion of music production and cognitive science has carved a transformative path in an era characterized by tremendous technical advancement and an ever-deepening understanding of the human brain. This essay investigates this ground-breaking nexus in an effort to unravel the complex interplay between brainwave patterns and acoustic components in music and its potential to radically alter musical creativity, production, and emotional resonance. The neurological underpinnings of music's psychological effects have been revealed by recent studies looking into the relationships between brainwave patterns and musical structures. Composers and producers can create songs that are artistically compelling and scientifically informed, capable of evoking desired emotional and cognitive reactions in listeners, by merging brainwave data with acoustic theory. This method also has the potential to be therapeutic, improving emotional wellbeing through cognitive rehabilitation and stress reduction. This research aims to broaden the understanding of the art of music and increase its ability to engage people on deeper cognitive and emotional levels as technology and methodology develop. Beyond the domain of traditional rhythms and notes, it explores the world of brainwaves, enhancing knowledge of the human condition through the transforming power of music.
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References
Karmakar S, Basu M, Sah N P, Choudhuri C D, Rana T K. Brainwave Sensing Device Based Musical Stress. 2019 3rd International Conference on Electronics, Materials Engineering & Nanotechnology (IEMENTech), Kolkata, India, 2019: 1-3.
Tai S K, Lin Y K. The influence of different kinds of music on brainwave signals. 2018 IEEE International Conference on Advanced Manufacturing (ICAM), Yunlin, Taiwan, 2018: 223-226.
Wang K J, Zheng C Y, Wairagkar M, von Mohr M. Jean Joseph ZERO: Let Memories Come to Life with Music. 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), Taoyuan, Taiwan, 2020: 1-2.
Desai B, Chen B, Sirocchi, McMullen K A. Mindtrack: Using brain-computer interface to translate emotions into music. 2018 International Conference on Digital Arts, Media and Technology (ICDAMT), Phayao, Thailand, 2018: 33-37.
Lee S H, Chen T Y, Hsien Y T, Cao L R. A Music Recommendation System for Depression Therapy Based on EEG. 2020 IEEE International Conference on Consumer Electronics - Taiwan (ICCE-Taiwan), Taoyuan, Taiwan, 2020: 1-2.
Treitler L. History and Music. New Literary History, 1990, 21(2): 299–319.
Chen S. Identification Model of Electronic Music Signal based on Optimization Group Algorithm. 2023 4th International Conference for Emerging Technology (INCET), Belgaum, India, 2023: 1-5.
Wang S, Yu W. Space Elements of Computer Music Production Based on VR Technology [. IEEE Access, 2020.
Chavan D R, Kumbhar M S, Chavan R R. The human stress recognition of brain, using music therapy. 2016 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC), Melmaruvathur, India, 2016: 200-203.
Thammasan N, Hagad J L, Fukui K, Numao M. Multimodal stability-sensitive emotion recognition based on brainwave and physiological signals. 2017 Seventh International Conference on Affective Computing and Intelligent Interaction Workshops and Demos (ACIIW), San Antonio, TX, USA, 2017: 44-49.
Liu L. Recognition and Analysis of Motor Imagery EEG Signal Based on Improved BP Neural Network," in IEEE Access, vol. 7, pp. 47794-47803, 2019, doi: 10.1109/ACCESS.2019.2910191.
Chavan D R, Kumbhar M S, Chavan R R. The human stress recognition of brain, using music therapy. 2016 International Conference on Computation of Power, Energy Information and Commuincation (ICCPEIC), Melmaruvathur, India, 2016: 200-203.
Liang L and Liu J. An exploration of the application of computer music production software in music composition. 2021 IEEE Asia-Pacific Conference on Image Processing, Electronics and Computers (IPEC), Dalian, China, 2021: 794-796.
Huang C F, Huang C Y. Emotion-based AI Music Generation System with CVAE-GAN. 2020 IEEE Eurasia Conference on IOT, Communication and Engineering (ECICE), Yunlin, Taiwan, 2020, 220-222.
Ramdinmawii E, Mittal V K. The effect of music on the human mind: A study using brainwaves and binaural beats. 2017 2nd International Conference on Telecommunication and Networks (TEL-NET), Noida, India, 2017: 1-7.
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