The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies

Ning Li; Jianchun Cai

doi:doi:10.11648/j.hss.20231106.16

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The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies

Ning Li, Jianchun Cai

Published in Humanities and Social Sciences (Volume 11, Issue 6)

Received: 6 November 2023 Accepted: 29 November 2023 Published: 29 November 2023

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Abstract

With the maturation of artificial intelligence technology, the swift advancements in music generation have spurred an in-depth exploration and comprehension of music aesthetics. This paper conducts a thorough analysis of the aesthetic framework, value, and significance inherent in artificial intelligence-based music generation algorithms. The technical architecture of these algorithms encompasses principles such as neural networks and genetic algorithms, they exhibit profound aesthetic potential, challenging existing perspectives and fundamentally reshaping the values embedded in music aesthetics. The aesthetic value of music generation algorithms resides in their capacity to produce music characterized by both beauty and novelty, this innovation manifests as a diversity suitable for various cultural contexts and stylistic preferences, thereby significantly enriching the landscape of music aesthetics. Moreover, this paper offers a forward-looking perspective on the intersection of artificial intelligence and music research. It foresees music generation algorithms taking the lead in the ongoing evolution of artificial intelligence technology, propelling innovations in composition and appreciation. These algorithms are poised to serve as a source of inspiration for creators, contributing significantly to education, cultural heritage, and redefining the very essence of music creation. This paper seeks to serve as a guiding resource for researchers in this field, fostering a deeper understanding of the profound impact that artificial intelligence-based music generation algorithms wield on the realm of music composition.

Published in	Humanities and Social Sciences (Volume 11, Issue 6)
DOI	10.11648/j.hss.20231106.16
Page(s)	223-230
Creative Commons	This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.
Copyright	Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Artificial Intelligence, Music Generation Algorithms, Music Aesthetics, Aesthetic Analysis

References

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[2]	Agarwal, P., Karnick, H., & Raj, B. A Comparative Study of Indian and Western Music Forms. Conference of the International Society for Music Information Retrieval (ISMIR). 4-8 Nov., Curitiba, Brazil, 2013.
[3]	Barton, G., Georgina B. The relationship between music, culture, and society: meaning in music. Music Learning and Teaching in Culturally and Socially Diverse Contexts: Implications for Classroom Practice, 2018, pp. 23-41.
[4]	Briot, J. P., Pachet, F. Music generation by deep learning-challenges and directions. arXiv preprint arXiv, 1712.04371, 2017.
[5]	Caramiaux, B., Donnarumma, M. Artificial intelligence in music and performance: a subjective art-research inquiry, Handbook of Artificial Intelligence for Music: Foundations, Advanced Approaches, and Developments for Creativity, 2021, pp. 75-95.
[6]	Carnovalini, F., Rodà, A. Computational creativity and music generation systems: An introduction to the state of the art. Frontiers in Artificial Intelligence, 2020 (3), 2020, pp. 14.
[7]	Dai, D. Artificial Intelligence Technology Assisted Music Teaching Design, Scientific Programming, 2021, pp. 1-10.
[8]	Kaliakatsos-Papakostas, M., Floros, A., & Vrahatis, M. N. Artificial intelligence methods for music generation: a review and future perspectives. Nature-Inspired Computation and Swarm Intelligence, 2020, pp. 217-245.
[9]	Miranda, E. R. Readings in music and artificial intelligence. Paris: Routledge. 2013.
[10]	S. Bennett. The Process of Musical Creation: Interviews with Eight Composers. Journal of Research in Music Education, 24(1), 1976, pp. 3-13.
[11]	S. Yuan. Application and Study of Musical Artificial Intelligence in Music Education Field. Journal of Physics: Conference Series, 1533 (2020), 2020, pp. 1-7.
[12]	Van De Haar, I., Broberg, C. P., & Doshoris, I. How Artificial Intelligence is changing The Relationship Between The Consumer and Brand in The Music Industry, Masters Paper, Lund University, 2019.
[13]	Walker, R. Music education: Cultural values, social change and innovation. Springfield: Charles C Thomas Publisher. 2007.
[14]	Xu, N., Zhao, Y. Online Education and Wireless Network Coordination of Electronic Music Creation and Performance under Artificial Intelligence. Wireless Communications and Mobile Computing, Vol. 2021, 2021, pp. 1-9.
[15]	Yang, F. Artificial intelligence in music education, 2020 International Conference on Robots & Intelligent System (ICRIS), 2020, pp. 483-484.
[16]	Yu, X., Ma, N., Zheng, L., et al. Developments and applications of artificial intelligence in music education, Technologies, 11(2), 2023, pp. 42.

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APA Style

Li, N., Cai, J. (2023). The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanities and Social Sciences, 11(6), 223-230. https://doi.org/10.11648/j.hss.20231106.16

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ACS Style

Li, N.; Cai, J. The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanit. Soc. Sci. 2023, 11(6), 223-230. doi: 10.11648/j.hss.20231106.16

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AMA Style

Li N, Cai J. The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanit Soc Sci. 2023;11(6):223-230. doi: 10.11648/j.hss.20231106.16

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@article{10.11648/j.hss.20231106.16,
  author = {Ning Li and Jianchun Cai},
  title = {The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies},
  journal = {Humanities and Social Sciences},
  volume = {11},
  number = {6},
  pages = {223-230},
  doi = {10.11648/j.hss.20231106.16},
  url = {https://doi.org/10.11648/j.hss.20231106.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hss.20231106.16},
  abstract = {With the maturation of artificial intelligence technology, the swift advancements in music generation have spurred an in-depth exploration and comprehension of music aesthetics. This paper conducts a thorough analysis of the aesthetic framework, value, and significance inherent in artificial intelligence-based music generation algorithms. The technical architecture of these algorithms encompasses principles such as neural networks and genetic algorithms, they exhibit profound aesthetic potential, challenging existing perspectives and fundamentally reshaping the values embedded in music aesthetics. The aesthetic value of music generation algorithms resides in their capacity to produce music characterized by both beauty and novelty, this innovation manifests as a diversity suitable for various cultural contexts and stylistic preferences, thereby significantly enriching the landscape of music aesthetics. Moreover, this paper offers a forward-looking perspective on the intersection of artificial intelligence and music research. It foresees music generation algorithms taking the lead in the ongoing evolution of artificial intelligence technology, propelling innovations in composition and appreciation. These algorithms are poised to serve as a source of inspiration for creators, contributing significantly to education, cultural heritage, and redefining the very essence of music creation. This paper seeks to serve as a guiding resource for researchers in this field, fostering a deeper understanding of the profound impact that artificial intelligence-based music generation algorithms wield on the realm of music composition.
},
 year = {2023}
}

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TY  - JOUR
T1  - The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies
AU  - Ning Li
AU  - Jianchun Cai
Y1  - 2023/11/29
PY  - 2023
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DO  - 10.11648/j.hss.20231106.16
T2  - Humanities and Social Sciences
JF  - Humanities and Social Sciences
JO  - Humanities and Social Sciences
SP  - 223
EP  - 230
PB  - Science Publishing Group
SN  - 2330-8184
UR  - https://doi.org/10.11648/j.hss.20231106.16
AB  - With the maturation of artificial intelligence technology, the swift advancements in music generation have spurred an in-depth exploration and comprehension of music aesthetics. This paper conducts a thorough analysis of the aesthetic framework, value, and significance inherent in artificial intelligence-based music generation algorithms. The technical architecture of these algorithms encompasses principles such as neural networks and genetic algorithms, they exhibit profound aesthetic potential, challenging existing perspectives and fundamentally reshaping the values embedded in music aesthetics. The aesthetic value of music generation algorithms resides in their capacity to produce music characterized by both beauty and novelty, this innovation manifests as a diversity suitable for various cultural contexts and stylistic preferences, thereby significantly enriching the landscape of music aesthetics. Moreover, this paper offers a forward-looking perspective on the intersection of artificial intelligence and music research. It foresees music generation algorithms taking the lead in the ongoing evolution of artificial intelligence technology, propelling innovations in composition and appreciation. These algorithms are poised to serve as a source of inspiration for creators, contributing significantly to education, cultural heritage, and redefining the very essence of music creation. This paper seeks to serve as a guiding resource for researchers in this field, fostering a deeper understanding of the profound impact that artificial intelligence-based music generation algorithms wield on the realm of music composition.

VL  - 11
IS  - 6
ER  -

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Author Information

Ning Li

Department of Music, Shenzhen University, Shenzhen, China

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Jianchun Cai

Department of Music, Shenzhen University, Shenzhen, China

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APA Style

Li, N., Cai, J. (2023). The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanities and Social Sciences, 11(6), 223-230. https://doi.org/10.11648/j.hss.20231106.16

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ACS Style

Li, N.; Cai, J. The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanit. Soc. Sci. 2023, 11(6), 223-230. doi: 10.11648/j.hss.20231106.16

Copy | Download

AMA Style

Li N, Cai J. The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies. Humanit Soc Sci. 2023;11(6):223-230. doi: 10.11648/j.hss.20231106.16

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@article{10.11648/j.hss.20231106.16,
  author = {Ning Li and Jianchun Cai},
  title = {The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies},
  journal = {Humanities and Social Sciences},
  volume = {11},
  number = {6},
  pages = {223-230},
  doi = {10.11648/j.hss.20231106.16},
  url = {https://doi.org/10.11648/j.hss.20231106.16},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.hss.20231106.16},
  abstract = {With the maturation of artificial intelligence technology, the swift advancements in music generation have spurred an in-depth exploration and comprehension of music aesthetics. This paper conducts a thorough analysis of the aesthetic framework, value, and significance inherent in artificial intelligence-based music generation algorithms. The technical architecture of these algorithms encompasses principles such as neural networks and genetic algorithms, they exhibit profound aesthetic potential, challenging existing perspectives and fundamentally reshaping the values embedded in music aesthetics. The aesthetic value of music generation algorithms resides in their capacity to produce music characterized by both beauty and novelty, this innovation manifests as a diversity suitable for various cultural contexts and stylistic preferences, thereby significantly enriching the landscape of music aesthetics. Moreover, this paper offers a forward-looking perspective on the intersection of artificial intelligence and music research. It foresees music generation algorithms taking the lead in the ongoing evolution of artificial intelligence technology, propelling innovations in composition and appreciation. These algorithms are poised to serve as a source of inspiration for creators, contributing significantly to education, cultural heritage, and redefining the very essence of music creation. This paper seeks to serve as a guiding resource for researchers in this field, fostering a deeper understanding of the profound impact that artificial intelligence-based music generation algorithms wield on the realm of music composition.
},
 year = {2023}
}

Copy | Download

TY  - JOUR
T1  - The Aesthetic Analysis of Music Generation Algorithms Based on Artificial Intelligence Technologies
AU  - Ning Li
AU  - Jianchun Cai
Y1  - 2023/11/29
PY  - 2023
N1  - https://doi.org/10.11648/j.hss.20231106.16
DO  - 10.11648/j.hss.20231106.16
T2  - Humanities and Social Sciences
JF  - Humanities and Social Sciences
JO  - Humanities and Social Sciences
SP  - 223
EP  - 230
PB  - Science Publishing Group
SN  - 2330-8184
UR  - https://doi.org/10.11648/j.hss.20231106.16
AB  - With the maturation of artificial intelligence technology, the swift advancements in music generation have spurred an in-depth exploration and comprehension of music aesthetics. This paper conducts a thorough analysis of the aesthetic framework, value, and significance inherent in artificial intelligence-based music generation algorithms. The technical architecture of these algorithms encompasses principles such as neural networks and genetic algorithms, they exhibit profound aesthetic potential, challenging existing perspectives and fundamentally reshaping the values embedded in music aesthetics. The aesthetic value of music generation algorithms resides in their capacity to produce music characterized by both beauty and novelty, this innovation manifests as a diversity suitable for various cultural contexts and stylistic preferences, thereby significantly enriching the landscape of music aesthetics. Moreover, this paper offers a forward-looking perspective on the intersection of artificial intelligence and music research. It foresees music generation algorithms taking the lead in the ongoing evolution of artificial intelligence technology, propelling innovations in composition and appreciation. These algorithms are poised to serve as a source of inspiration for creators, contributing significantly to education, cultural heritage, and redefining the very essence of music creation. This paper seeks to serve as a guiding resource for researchers in this field, fostering a deeper understanding of the profound impact that artificial intelligence-based music generation algorithms wield on the realm of music composition.

VL  - 11
IS  - 6
ER  -

Copy | Download