After completion of the course, the student:|
- has obtained an overview of the field of digital humanities;
- has obtained basic understanding of computing science and computational modeling;
- has obtained basic understanding of data mining and the broader field of artificial intelligence;
- has obtained an overview of the field of music information retrieval;
- has obtained an overview of historical and current developments in computational musicology within the context of digital humanities;
- has developed a critical view on current computational research methods from a musicological and a humanities point of view;
- has learnt to identify possibilities for computational methods in musicological and humanities-related research.
By accomplishing these goals you will gain realistic expectations of digital tools and be able to take an informed position in the emerging field of digital humanities, separating the chaff from the wheat.
This course is for students in the RMA Musicology; students from the RMA programmes Art History and MAPS should check with the course coordinator by email before enrolling November 28th at the latest. Only this way participation can be granted. The entrance requirements for Exchange Students will be checked by International Office and the Programme coordinator. You do not have to contact the Programme coordinator by yourself.|
This course provides an overview of current developments in digital musicology within the larger context of digital humanities. A basic introduction to computing and information science as well as a basic introduction to empirical research methodologies is part of the course. Understanding the computer as a machine and as tool will explicitly be addressed. The broader field of digital humanities will be surveyed, and the unique opportunities and challenges specific to musicological inquiry highlighted. Topics such as music information retrieval, computational ethnomusicology, digital music representations and visualizations, computational models of music cognition, performance modeling, and digital editions will be discussed alongside topics from digital humanities in general. The concepts of tool, model, and modeling will be of central importance. These are related to two fundamentally different kinds of computer-aided research. We will spend considerable time on understanding data mining, which comprises a variety of methods – from naive classifiers to deep learning – to automatically construct a generalized model from a (large) number of example objects. This paradigm underlies many computational music studies.
Career orientation: |
Training in written and oral presentation of research, training in computer-based research methods, understanding computers as research tools.