Machine Learning for Musical Expression: A Systematic Literature Review

Théo Jourdan, and Baptiste Caramiaux

Proceedings of the International Conference on New Interfaces for Musical Expression

  • Year: 2023
  • Location: Mexico City, Mexico
  • Track: Papers
  • Pages: 319–331
  • Article Number: 46
  • PDF link

Abstract:

For several decades NIME community has always been appropriating machine learning (ML) to apply for various tasks such as gesture-sound mapping or sound synthesis for digital musical instruments. Recently, the use of ML methods seems to have increased and the objectives have diversified. Despite its increasing use, few contributions have studied what constitutes the culture of learning technologies for this specific practice. This paper presents an analysis of 69 contributions selected from a systematic review of the NIME conference over the last 10 years. This paper aims at analysing the practices involving ML in terms of the techniques and the task used and the ways to interact this technology. It thus contributes to a deeper understanding of the specific goals and motivation in using ML for musical expression. This study allows us to propose new perspectives in the practice of these techniques.

Citation:

Théo Jourdan, and Baptiste Caramiaux. 2023. Machine Learning for Musical Expression: A Systematic Literature Review. Proceedings of the International Conference on New Interfaces for Musical Expression. DOI:

BibTeX Entry:

  @article{nime2023_46,
 abstract = {For several decades NIME community has always been appropriating machine learning (ML) to apply for various tasks such as gesture-sound mapping or sound synthesis for digital musical instruments. Recently, the use of ML methods seems to have increased and the objectives have diversified. Despite its increasing use, few contributions have studied what constitutes the culture of learning technologies for this specific practice. This paper presents an analysis of 69 contributions selected from a systematic review of the NIME conference over the last 10 years. This paper aims at analysing the practices involving ML in terms of the techniques and the task used and the ways to interact this technology. It thus contributes to a deeper understanding of the specific goals and motivation in using ML for musical expression. This study allows us to propose new perspectives in the practice of these techniques.},
 address = {Mexico City, Mexico},
 articleno = {46},
 author = {Théo Jourdan and Baptiste Caramiaux},
 booktitle = {Proceedings of the International Conference on New Interfaces for Musical Expression},
 editor = {Miguel Ortiz and Adnan Marquez-Borbon},
 issn = {2220-4806},
 month = {May},
 numpages = {13},
 pages = {319--331},
 title = {Machine Learning for Musical Expression: A Systematic Literature Review},
 track = {Papers},
 url = {http://nime.org/proceedings/2023/nime2023_46.pdf},
 year = {2023}
}