The world of music has changed for good in the digital age. This revolution must be matched by a transformation of the means by which music is studied. While preserving the best traditional values and practices of musicology we can take advantage of the immense opportunities offered by music information retrieval (MIR).
Transforming Musicology seeks to explore how emerging technologies for working with music as sound and score can transform musicology, both as an academic discipline and as a practice outside the university.
Our objectives therefore include to:
- Effect a Digital Transformation of Musicology by incorporating powerful methods developed over more than a decade of MIR, a multi-disciplinary field hitherto perceived as just serving the music industry, but partly arising from the vision of music librarians and musicologists of the digital future.
- Carry out necessary changes to existing MIR tools to optimise them for musicology.
- Demonstrate, in three parallel musicological investigations, the value of MIR tools, suitably applied, and their potential for musicology:
- Enhance and strengthen the evidential base for traditional study using encodings of 16th-century vocal and lute music from ECOLM3 as the subject of new MIR pattern-matching analyses; also comparison with audio recordings, both commercial and self-recorded by a community of lute experts.
- Augment the methods of a standard musicological approach to the study of Wagner's leitmotifs by using MIR tools on recordings and (as possible) on encoded scores; psychologically test the ability of people to recognise leitmotifs on their own and in an orchestral context.
- Innovate by introducing an entirely new kind of musicology of the social media combining the use of MIR tools with social network analysis to show (e.g.) how musical phenomena are adopted and spread through the huge online community.
- Ensure sustainability and repeatability by embedding the above research activities in a framework enabling data, methods and results to be shared permanently as Linked Data.
- Enhance Semantic Web workflow description methods for musicology, adapting to the needs of the research as they emerge in the project.
We also run a one week workshop on Digital Musicology at the Digital Humanities at Oxford Summer School.