Creaciones artísticas musicales e Inteligencia Artificial (2019-2022)

Jenny P. Lis Gutiérrez; Jhonathan S. Pulido-Flórez

doi:10.34096/oidopensante.v12n1.12176

Jenny P. Lis Gutiérrez Fundación Universitaria Konrad Lorenz https://orcid.org/0000-0002-1438-7619
Jhonathan S. Pulido-Flórez Fundación Universitaria Konrad Lorenz https://orcid.org/0000-0002-2797-2278

DOI: https://doi.org/10.34096/oidopensante.v12n1.12176

Keywords: Artificial Intelligence, music, intellectual property, artistic creation, musical artistic creation

Abstract

The aim of this research is to analyze how Artificial Intelligence was used in music artistic creation between the years 2019 and 2022. For this purpose, three key aspects were addressed: (i) describing the different uses of Artificial Intelligence in the musical domain, (ii) examining the advantages and disadvantages of its application, and (iii) comparing three specific cases of Artificial Intelligence implementation in music (Massive Attack, DeepBeat, These Lyrics Do Not Exist). A qualitative methodology was employed, involving an exhaustive review of scientific literature and a detailed analysis of primary sources related to the mentioned cases. Through this process, it was identified that Artificial Intelligence has been increasingly used in various musical aspects, encompassing composition, musical instruction, and recommendation, with a significant impact on the commercial sphere. Additionally, the use of Artificial Intelligence in music has demonstrated diverse advantages and disadvantages in areas such as convenience, creativity, autonomy, intellectual property, investment, technological development, flexibility, and musical writing. Furthermore, the detailed comparison of the three cases studied allowed for the identification of the scope and concrete applications of Deep Learning in the musical domain, showcasing its wide adoption and massive utilization in this field. An important aspect arising from this research is its contribution to the discussion on new scenarios and the development of policies and regulations in the realm of artistic creation involving Artificial Intelligence.

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Author Biographies

Jenny P. Lis Gutiérrez, Fundación Universitaria Konrad Lorenz

Doctora en Ingeniería – Industria y Organizaciones (Universidad Nacional de Colombia, Bogotá-Colombia), Magister en Análisis de Problemas Políticos, Económicos e Internacionales (Universidad Externado e Instituto de Altos Estudios para el Desarrollo, Bogotá-Colombia. Tesis meritoria). Magister en «sociétés contemporaines comparées Europe – Amérique latine»(Université Paris III – Sorbonne Nouvelle Paris, Francia), spécialité géographie, aménagement et urbanisme (Institut des Hautes Etudes de l'Amérique latine – IHEAL, Paris, Francia. Tesis meritoria), Especialista en Estadística Aplicada (Fundación Universitaria Los Libertadores, Bogotá-Colombia. Trabajo de grado laureada), Especialista en Evaluación y Formulación de Proyectos (IUD, Medellín, Colombia), Economista graduada con honores (Universidad Nacional de Colombia, Bogotá-Colombia).

Jhonathan S. Pulido-Flórez, Fundación Universitaria Konrad Lorenz

Investigador en formación Fundación Universitaria Konrad Lorenz y Bioecoval.

References

Abeliuk, A. y Gutiérrez, C. (2021). Historia y evolución de la Inteligencia Artificial. Revista Bits de Ciencia, 21, 14-21. Recuperado de https://revistasdex.uchile.cl/index.php/bits/article/download/2767/2700

Amstrong, S. (2019, 15 marzo). With AI and DNA, Massive Attack are Hacking a New Kind of Music. Wired. Recuperado de https://www.wired.co.uk/article/massive-attack-mezzanine-dna

Andrés, G. D., San Martín, P. S. y Lujan Rodríguez, G. (2023). Análisis multidimensional de la sostenibilidad-DID en el contexto físico-virtual. Cuadernos.info, 54, 1-22. doi: https://dx.doi.org/10.7764/cdi.54.52515

Ben-Tal, O., Harris, M. T. y Sturm, B. L. (2021). How Music AI Is Useful: Engagements with Composers, Performers and Audiences. Leonardo, 54(5), 510-516. doi: https://doi.org/10.1162/leon_a_01959

Briot, J. P. (2021). From Artificial Neural Networks to Deep Learning for Music Generation: History, Concepts, and Trends. Neural Computing & Applications, 33(1), 39-65. doi: https://doi.org/10.1007/s00521-020-05399-0

Briot, J., Hadjeres, G. y Pachet, F. (2020). Deep Learning Techniques for Music Generation. In Computational Synthesis and Creative Systems. Springer. doi: https://doi.org/10.1007/978-3-319-70163-9

Castelli, M. y Manzoni, L. (2022). Special Issue: Generative Models in Artificial Intelligence and their Applications. Applied Sciences, 12(9), 4127. doi: https://doi.org/10.3390/app12094127

Chen, F. y Meng, H. (2022). The Use of Wireless Network Combined with Artificial Intelligence Technology in the Reform of Music Online Teaching System. Wireless Communications and Mobile Computing, 2022, 1-10. doi: https://doi.org/10.1155/2022/5957708

Choi, K., Park, J., Heo, W., Jeon, S. y Park, J. (2021). Chord Conditioned Melody Generation with Transformer Based Decoders. IEEE Access, 9, 42071-42080. Recuperado de https://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=9376975

Civit, M., Civit-Masot, J., Cuadrado, F. y Cuaresma, M. J. E. (2022). A Systematic Review of Artificial Intelligence-based Music Generation: Scope, Applications, and Future Trends. Expert Systems with Applications, 209, 118-190. doi: https://doi.org/10.1016/j.eswa.2022.118190

Corvalán, J. G. (2018). Inteligencia Artificial: retos, desafíos y oportunidades. Prometea: la primera Inteligencia Artificial de Latinoamérica al servicio de la Justicia. Revista de Investigações Constitucionais, 5(1), 297. doi: https://doi.org/10.5380/rinc.v5i1.55334

De Prisco, R., Guarino, A., Lettieri, N., Malandrino, D. y Zaccagnino, R. (2021). Providing Music Service in Ambient Intelligence: Experiments with Gym Users. Expert Systems with Applications, 177, 1-19. doi: https://doi.org/10.1016/j.eswa.2021.114951

Doush, I. y Sawalha, A. (2020). Automatic Music Composition Using Genetic Algorithm and Artificial Neural Networks. Malaysian Journal of Computer Science, 33(1), 35-51. doi: https://doi.org/10.22452/mjcs.vol33no1.3

Drott, E. (2020). Copyright, Compensation, and Commons in the Music AI industry. Creative Industries Journal, 14(2), 190-207. doi: https://doi.org/10.1080/17510694.2020.1839702

Fan, X. y Zhong, X. (2022). Artificial Intelligence-based Creative Thinking Skill Analysis Model Using Human–computer Interaction in Art Design Teaching. Computers and Electrical Engineering, 100, 1-16. doi: https://doi.org/10.1016/j.compeleceng.2022.107957

Feng, X. Q. y Pan, B. H. (2021). The Evolution of Patent System: Invention Created by Artificial Intelligence. Procedia Computer Science, 183, 245-253. doi: https://doi.org/10.1016/j.procs.2021.02.055

Hertzmann, A. (2020). Computers do not Make Art, People Do. Communications of the ACM, 63(5), 45-48. doi: https://doi.org/10.1145/3347092

Hong, J. W., Fischer, K., Ha, Y. y Zeng, Y. (2022). Human, I Wrote a Song for You: An Experiment Testing the Influence of Machines’ Attributes on the AI-composed Music Evaluation. Computers in Human Behavior, 131, 1-12. doi: https://doi.org/10.1016/j.chb.2022.107239

Kaliakatsos-Papakostas, M., Floros, A. y Vrahatis, M. N. (2020). Artificial Intelligence Methods for Music Generation: A Review and Future Perspectives. Nature-Inspired Computation and Swarm Intelligence, 217-245. doi: https://doi.org/10.1016/b978-0-12-819714-1.00024-5

KDD2016. (2016, Junio 30). KDD2016 paper 819 [Video]. YouTube. https://www.youtube.com/watch?v=Vbaf9yJ6HBc&t=2s

Kumar, L., Goyal, P. y Kumar, R. (2020). Creativity in Machines: Music Composition Using Artificial Intelligence. Asian Journal of Convergence in Technology, 6(2), 36-40. doi: https://doi.org/10.33130/ajct.2020v06i02.007

Malmi, E., Takala, P., Toivonen, H., Raiko, T. y Gionis A. (2015). DopeLearning: A Computational Approach to Rap Lyrics Generation. Recuperado de https://arxiv.org/pdf/1505.04771v1.pdf

McPherson, A. y Tahıroğlu, K. (2020). Idiomatic Patterns and Aesthetic Influence in Computer Music Languages. Organised Sound, 25(1), 53-63. doi: https://doi.org/10.1017/s1355771819000463

Miao, D., Lu, X., Dong, Q. y Hong, D. (2020). Humming-Query and Reinforcement-Learning Based Modeling Approach for Personalized Music Recommendation. Procedia Computer Science, 176, 2154-2163. doi: https://doi.org/10.1016/j.procs.2020.09.252

Muhamed, A., Li, L., Shi, X., Yaddanapudi, S., Chi, W., Jackson, D., Suresh, R., Lipton, Z. C. y Smola, A. J. (2021). Symbolic Music Generation with Transformer-GANs. Proceedings of the AAAI Conference on Artificial Intelligence, 35(1), 408 417. doi: https://doi.org/10.1609/aaai.v35i1.16117

Navarro, M. C., Oliveira, H. G., Martins, P. y Cardoso, A. (2020). Integration of a Music Generator and a Song Lyrics Generator to Create Spanish Popular Songs. Journal of Ambient Intelligence and Humanized Computing, 11(11), 4421-4437. doi: https://doi.org/10.1007/s12652-020-01822-5

Plut, C. y Pasquier, P. (2020). Generative Music in Video Games: State of the Art, Challenges, and Prospects. Entertainment Computing, 33, 1-19. doi: https://doi.org/10.1016/j.entcom.2019.100337

Rodgers, W., Yeung, F., Odindo, C.y Degbey, W. Y. (2021). Artificial Intelligence-Driven Music Biometrics Influencing Customers’ Retail Buying Behavior. Journal of Business Research, 126, 401-414. doi: https://doi.org/10.1016/j.jbusres.2020.12.039

Rakhmatullaev, H. S. (2022). Music, Man and Artificial Intelligence. Central Asian Journal of Social Sciences and History, 3(12), 93-96. Recuperado de https://cajssh.centralasianstudies.org/index.php/CAJSSH/article/view/540

Rouhiainen, L. P. (2018). Inteligencia Artificial. 101 Cosas que debes saber hoy sobre nuestro futuro. Alienta Editorial. Recuperado de https://static0planetadelibroscom.cdnstatics.com/libros_contenido_extra/40/39308_Inteligencia_artificial.pdf

Salem, A., El-Horbaty, E. y Siphocly, N. (2019). Analysis of Computational Intelligent Techniques of Music Generation. Egyptian Computer Science Journal, 43, 49-64. Recuperado de http://ecsjournal.org/Archive/Volume43/Issue3/4.pdf

Schmidt, P., Biessmann, F. y Teubner, T. (2020). Transparency and Trust in Artificial Intelligence Systems. Journal of Decision Systems, 29(4), 260-278. doi: https://doi.org/10.1080/12460125.2020.1819094

Steels, L. y Lopez De Mantaras, R. (2018). The Barcelona Declaration for the Proper Development and Usage of Artificial Intelligence in Europe. AI Communications, 31(6), 485-494. doi: https://doi.org/10.3233/aic-180607

Sturm, B. L. T., Iglesias, M., Ben-Tal, O., Miron, M. y Gómez, E. (2019). Artificial Intelligence and Music: Open Questions of Copyright Law and Engineering Praxis. Arts, 8(3), 115. doi: https://doi.org/10.3390/arts8030115

Tahiroğlu, K. (2021). Ever-Shifting Roles in Building, Composing, and Performing with Digital Musical Instruments. Journal of New Music Research, 50(2), 155-164. doi: https://doi.org/10.1080/09298215.2021.1900275

The Economist. (2018, 28 Marzo). Non-Tech Businesses are Beginning to Use Artificial Intelligence at Scale. Recuperado de https://www.economist.com/special-report/2018/03/28/non-tech-businesses-are-beginning-to-use-artificial-intelligence-at-scale

These Lyrics do not Exist. (2022). Lyrics Generated Using Artificial Intelligence. Recuperado de https://theselyricsdonotexist.com/

Wei, J., Marimuthu, K. y Prathik, A. (2022). College Music Education and Teaching Based on AI Techniques. Computers and Electrical Engineering, 100, 6-9. doi: https://doi.org/10.1016/j.compeleceng.2022.107851

Yang, J. (2021). Research on the Artificial Intelligence Teaching System Model for Online Teaching of Classical Music under the Support of Wireless Networks. Wireless Communications and Mobile Computing, 2021, 1-11. doi: https://doi.org/10.1155/2021/4298439

Zhang, W., Shankar, A., and Antonidoss, A. (2021). Modern Art Education and Teaching Based on Artificial Intelligence. Journal of Interconnection Networks, 22(Supp01). doi: https://doi.org/10.1142/s021926592141005x

Musical Artistic Creations and Artificial Intelligence (2019-2022)

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References