Music and Artificial Intelligence
Music and Artificial Intelligence (MoKI)
This research and development group is based on the growing field where music meets artificial intelligence (AI), with the goal of exploring how AI can contribute to new forms of artistic practices, interaction, and reflection, with a primary focus on music. The group brings together performing musicians, sound artists, composers, technologists, researchers, and students in an interdisciplinary environment, facilitating experimentation, development, and critical discussion, as well as creative collaboration between humans and AI-based technologies.
Music is one of the most complex and expressive human activities, and AI opens up new ways to understand, create, and communicate music. The group will investigate how AI can be used as a co-creative tool in composition and improvisation, as a tool and therapeutic resource in health and wellness contexts involving music, and as a tool for understanding musical structures and processes. The group will also examine the aesthetic, ethical, and cultural implications of integrating intelligent systems into artistic work.
Activities:
- Workshops focused on real-time interaction between musicians and AI systems
- Development of tools for generative music and interactive sound
- Artistic projects and performances exploring human-machine relationships
- Symposium associated with MishMash – Centre for AI and Creativity
- Academic seminars and publications highlighting artistic, theoretical, and methodological perspectives
- Interdisciplinary teaching and mentoring for students and PhD candidates in music technology and artistic research
Projects, Networks, and Centers We Are Involved In:
- MishMash Centre for AI and Creativity
- Rhythm and Intentionality in Computer Assisted Musicmaking
- MotionComposer
The R&D group will also contribute to building networks between educational and research institutions, artistic communities, and technological stakeholders, both nationally and internationally.
The group has access to a PC with a GPU tailored for training machine learning models.
Group leader / contact person
Participants
-
Øyvind Brandtsegg Professor
+47-73590095 +4792203205 oyvind.brandtsegg@ntnu.no Department of Music -
Trond Engum Professor
+47-73590092 trond.engum@ntnu.no Department of Music -
Daniel Buner Formo Associate Professor
+47-73590097 daniel.formo@ntnu.no Department of Music -
Heather Frasch Professor
heather.frasch@ntnu.no Department of Music -
Gunnar Tufte Professor; Deputy Head of Department (Research); Head of the PhD Program in Computer Science
+47-73590356 +4797402478 gunnar.tufte@ntnu.no Department of Computer Science