The Music, Science and Technology Research Cluster (MSTRC) at the Department of Music comprises an international and interdisciplinary community of staff and research students working in areas across music, science and technology.

The research cluster aims to:

  • Study music perception and cognition, musical behaviour and music experience using scientific methods and emerging technologies
  • Develop technology for musical application based on the integration of artistic, scientific and engineering knowledge
  • Study the application of technology in music composition, performance, recording, reproduction, dissemination and consumption
  • Critically examine the interactions between technology, culture, business, and creativity

The research cluster boasts outstanding facilities, a seminar series, a supportive community of interdisciplinary researchers, and a thriving environment that benefits from the broader musical activities of the department. The MSTRC continuously interacts and collaborates with other research clusters at the Department of Music, other Departments at the University of York, and other institutions internationally.

Projects

Aesthetic judgement and emotional processing of contemporary music

Understanding why listeners respond differently to contemporary music.

Persona

Gazelle Twin extends her music across film, visual effects, theatre, immersive and spatial sound.

Experimental concert research

Examining what makes a classical concert.

Turning the inside out

Exploring whether facial expressions of emotion help predict experienced emotions in music.

See more projects

Groups

The Music, Science and Technology Cluster has four groups that complete research and explore the topic in more detail.

The Music Computing and Psychology Lab

The lab is internationally renowned for its work on the development and application of AI in both music-making and music-analytic scenarios. We address research topics including human-computer co-creativity; AI music for games and screen media; pattern discovery in music; fundamentals of and formats for music representation, analysis, and manipulation; natural language processing for music; music cognition; AI for web audio and podcasting.