Comparison of Music Composing Software: Amper Music, MLstudio and AIVA
Research Article
Open Access
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Comparison of Music Composing Software: Amper Music, MLstudio and AIVA

Anri Si Tong Yan 1*
1 Walnut Hill School for the Arts, Natick, the United States
*Corresponding author: anriyanst813@gmail.com
Published on 4 July 2025
Volume Cover
ACE Vol.166
ISSN (Print): 2755-273X
ISSN (Online): 2755-2721
ISBN (Print): 978-1-80590-177-8
ISBN (Online): 978-1-80590-178-5
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Abstract

As a matter of, music composition has been witnessed rapid developments on account of the development of computing ability. On this basis, various music composing software has been developed that help to compose music with better user surfaces, functions as well as agile generation. With this in mind, this study detailly analyzes three specific composing software, i.e., Amper Music, MLstudio and AIVA. According to the analysis, the functions, principles and applications for the three software will be demonstrated. At the same time, the current drawbacks of the software will also be discussed. In the meantime, the future prospects for the software will also be proposed. Based on the evaluations, these platforms are expected to evolve with deeper emotional modeling, real-time interactivity, and broader integration of generative audio capabilities and may shape the future of both music production and human-AI collaboration. Overall, these results shed light on guiding further exploration of music composing.

Keywords:

Music composing, Amper Music, MLstudio, AIVA.

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Yan,A.S.T. (2025). Comparison of Music Composing Software: Amper Music, MLstudio and AIVA. Applied and Computational Engineering,166,169-176.

References

[1]. Maganioti, A.E., Chrissanthi, H.D., Charalabos, P.C., Andreas, R.D., George, P.N. and Christos, C.N. (2010)

[2]. Verma, S. (2021) Artificial intelligence and music: History and the future perceptive. International Journal of Applied Research, 7(2), 272-275.

[3]. Hiller, L. (2025) Electronic music. In Encyclopedia Britannica.

[4]. Ji, S., Luo, J. and Yang, X. (2020) A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions.  arXiv preprint arXiv: 2011.06801.

[5]. Jarrett, S. and Day, H. (2024) Music composition for dummies. John Wiley & Sons.

[6]. Efe, M. The History of Artificial Intelligence in Music. MÜZİK ve GÜZEL SANATLAR EĞİTİMİ, 33.

[7]. Fox, M., Vaidyanathan, G. and Breese, J.L. (2024) The impact of artificial intelligence on musicians. Issues in Information Systems, 25(3).

[8]. Martin, E. and Avila Rojas, L. O. (2022) Tools for AI Music Creatives: Mapping the field.

[9]. Gera, S. (2025) The Impact of Artificial Intelligence on Music Production: Creative Potential, Ethical Dilemmas, and the Future of the Industry.

[10]. Geelen, T.V. (2020) Motivations for using Artificial Intelligence in the popular music composition and production process (Master's thesis).

[11]. Milošević, M., Lukić, D., Ostojić, G., Lazarević, M., and Antić, A. (2022) Application of cloud-based machine learning in cutting tool condition monitoring. Journal of Production Engineering, 20-24.

[12]. Borra, P. (2024) Advancing data science and AI with azure machine learning: A comprehensive review. International Journal of Research Publication and Reviews, 5(6), 1825-1831.

[13]. Turgay, E. Y. (2024) The Use of Artificial Intelligence Techniques for the Creation of Soundtracks from Videos.

[14]. Karpov, N. (2020) Artificial Intelligence for Music Composing: Future Scenario Analysis.

[15]. Frid, E., Gomes, C. and Jin, Z. (2020) Music creation by example. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-13).

References

[1]. Maganioti, A.E., Chrissanthi, H.D., Charalabos, P.C., Andreas, R.D., George, P.N. and Christos, C.N. (2010)

[2]. Verma, S. (2021) Artificial intelligence and music: History and the future perceptive. International Journal of Applied Research, 7(2), 272-275.

[3]. Hiller, L. (2025) Electronic music. In Encyclopedia Britannica.

[4]. Ji, S., Luo, J. and Yang, X. (2020) A comprehensive survey on deep music generation: Multi-level representations, algorithms, evaluations, and future directions.  arXiv preprint arXiv: 2011.06801.

[5]. Jarrett, S. and Day, H. (2024) Music composition for dummies. John Wiley & Sons.

[6]. Efe, M. The History of Artificial Intelligence in Music. MÜZİK ve GÜZEL SANATLAR EĞİTİMİ, 33.

[7]. Fox, M., Vaidyanathan, G. and Breese, J.L. (2024) The impact of artificial intelligence on musicians. Issues in Information Systems, 25(3).

[8]. Martin, E. and Avila Rojas, L. O. (2022) Tools for AI Music Creatives: Mapping the field.

[9]. Gera, S. (2025) The Impact of Artificial Intelligence on Music Production: Creative Potential, Ethical Dilemmas, and the Future of the Industry.

[10]. Geelen, T.V. (2020) Motivations for using Artificial Intelligence in the popular music composition and production process (Master's thesis).

[11]. Milošević, M., Lukić, D., Ostojić, G., Lazarević, M., and Antić, A. (2022) Application of cloud-based machine learning in cutting tool condition monitoring. Journal of Production Engineering, 20-24.

[12]. Borra, P. (2024) Advancing data science and AI with azure machine learning: A comprehensive review. International Journal of Research Publication and Reviews, 5(6), 1825-1831.

[13]. Turgay, E. Y. (2024) The Use of Artificial Intelligence Techniques for the Creation of Soundtracks from Videos.

[14]. Karpov, N. (2020) Artificial Intelligence for Music Composing: Future Scenario Analysis.

[15]. Frid, E., Gomes, C. and Jin, Z. (2020) Music creation by example. In Proceedings of the 2020 CHI conference on human factors in computing systems (pp. 1-13).

Cite this article

Yan,A.S.T. (2025). Comparison of Music Composing Software: Amper Music, MLstudio and AIVA. Applied and Computational Engineering,166,169-176.

Data availability

The datasets used and/or analyzed during the current study will be available from the authors upon reasonable request.

About volume

Volume title: Proceedings of CONF-SEML 2025 Symposium: Machine Learning Theory and Applications

ISBN: 978-1-80590-177-8(Print) / 978-1-80590-178-5(Online)
Editor: Hui-Rang Hou
Conference website: https://2025.confseml.org/tianjin.html
Conference date: 18 May 2025
Series: Applied and Computational Engineering
Volume number: Vol.166
ISSN: 2755-2721(Print) / 2755-273X(Online)

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