Comparison of Music Composing Software: Amper Music, MLstudio and AIVA

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.

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Publication Details

Journal
Applied and Computational Engineering
Published
2025-07-04
DOI
https://doi.org/10.54254/2755-2721/2025.tj24667
Primary Topic
Music Technology and Sound Studies
Type
article
Field-Weighted Citation Impact
0.00
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article

Comparison of Music Composing Software: Amper Music, MLstudio and AIVA

Anri Si Tong Yan
Applied and Computational Engineering
Music Technology and Sound Studies
article

Comparison of Music Composing Software: Amper Music, MLstudio and AIVA

Anri Si Tong Yan
article en

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.

Applied and Computational EngineeringVol. 166(1)
The Restaurant School at Walnut Hill College (US)
Openalex Percentile: Top 85%
Music Technology and Sound Studies
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