Digital musicology
Summary
This course will introduce students to the central topics in digital musicology and core theoretical approaches and methods. In the practical part, students will carry out a number of exercises.
Content
Digital Musicology (DM) is a vibrant field which studies music, its properties and its development across genres, times, historical traditions and cultures. The digital humanities revolution with its data-driven methods has initiated a paradigmatic shift in musicology, making it possible to tap into musical corpora of unprecedented size and often reveal new kinds of evidence. Since music is in essence a phenomenon of the human mind, the field combines methods from music theory, psychology, data science and computational modeling. This class will offer an introduction into DM, its central questions, methods and the state-of-the-art. It is structured around the core parameters of music and surveys some of the main ways of exploring them theoretically, cognitively and computationally.
The class will be complemented with a series of exercises that students will carry out.
Course topics include:
- Core research questions in DM
- Musical corpora, representation, and transmission
- Psychoacoustic foundations
- Rhythm, meter, expressive timing, groove
- Tuning, scales and modes
- Models of tonal pitch, tonal space, models of tonality
- Melodic shape and structure
- Musical expectancy and predictive processing
- Combining notes and polyphony
- Chords and harmony
- Musical form and musical grammar
- Cultures, histories, geographies and networks
- Music aesthetics and philosophy
Keywords
music, digital humanities, musicology, music theory, data science, music cognition
Learning Prerequisites
Required courses
Required course (obligatory):
- Foundations of algebra, statistics and data analysis
- Basic programming (e.g. Python, Julia)
Recommended courses
Recommended background:
Important concepts to start the course
Prior knowledge of music theory (e.g. notation, scales, chords) is desirable and beneficial, but the class can be completed without it.
Students with little or no experience in score reading may consult introductory texts such as:
- Henry, E., Snodgrass, J., and Piagentini, S. (2019). Fundamentals of music: Rudiments, musicianship, and composition, 7th ed., Pearson.
- Taylor, E. R. (1999). The AB guide to music theory. 5 vols. Associated Board of the Royal Schools of Music.
Students with musical backgrounds will rather benefit from a harmony textbook, for example:
- Laitz, S.G. (2003). The complete musician: an integrated approach to tonal harmony, analysis, and listening. Oxford University Press.
- Gauldin, R. (1997). Harmonic practice in tonal music. Norton & Company.
For online introductions, see for instance:
- https://www.musictheory.net/lessons
- http://musictheory.pugetsound.edu/mt21c/MusicTheory.html
Learning Outcomes
By the end of the course, the student must be able to:
- Distinguish the core concepts used in digital musicology
- Explore and orient themselves in the multidisciplinary field and identify important research questions and methods
- Analyze databases containing musical and contextual data (e.g. corpora of pieces or metadata)
- Develop hypotheses about music and musical structures
- Assess / Evaluate their hypotheses with computational models
- Interpret results of their models in the context of the field
- Defend their research in discussion with peers
Transversal skills
- Set objectives and design an action plan to reach those objectives.
- Use a work methodology appropriate to the task.
- Assess progress against the plan, and adapt the plan as appropriate.
- Plan and carry out activities in a way which makes optimal use of available time and other resources.
- Communicate effectively, being understood, including across different languages and cultures.
- Take feedback (critique) and respond in an appropriate manner.
- Write a scientific or technical report.
Teaching methods
The course teaching consists of weekly lectures that will cover core topics, concepts and methods. In addition, it will include tutorials, research paper discussion and feedback on exercises.
Expected student activities
Students are expected to attend the class regularly and actively complete the exercises. Students are also required to fulfill the reading assignments.
Assessment methods
1. Active participation in class.
2. Exercises assigned during the class.
Supervision
Office hours | Yes |
Assistants | Yes |
Forum | Yes |
In the programs
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Digital musicology
- Lecture: 3 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Type: mandatory
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Digital musicology
- Lecture: 3 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Type: mandatory
- Exam form: During the semester (summer session)
- Subject examined: Digital musicology
- Lecture: 3 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Digital musicology
- Lecture: 3 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Type: optional
- Semester: Spring
- Exam form: During the semester (summer session)
- Subject examined: Digital musicology
- Lecture: 3 Hour(s) per week x 14 weeks
- Project: 2 Hour(s) per week x 14 weeks
- Type: optional
Reference week
Mo | Tu | We | Th | Fr | |
8-9 | |||||
9-10 | |||||
10-11 | |||||
11-12 | |||||
12-13 | |||||
13-14 | |||||
14-15 | |||||
15-16 | |||||
16-17 | |||||
17-18 | |||||
18-19 | |||||
19-20 | |||||
20-21 | |||||
21-22 |
Légendes:
Lecture
Exercise, TP
Project, labs, other