An Introduction to Digital Musicology 3106-WMC-FO
The primary objective of the course is to introduce students to the history
of digital musicology, to familiarise them with potential developments in
the field and the different methodological orientations. Students will be
introduced to the most significant music coding languages, such as
Humdrum, EsAC and MEI, as well as to the analytical tools for automated
extraction of analytical data (including music21, Music Processing Suite,
DiMCAT, Humdrum, HumdrumR).
The course will also address key digital repositories and the various types
of music corpora, along with the research perspectives that emerge from
their exploration. The course will introduce students to analytical tools
designed for the analysis of Humdrum **kern music collections and will
instruct them in the utilisation of these tools for the analysis of both
individual works and the comparative analysis of extensive music
corpora.
The practical element of the course will entail the analysis of prominent
collections such as The Essen Folksong Collection, the comparative
analysis of ballads from this collection and ballads collected by Oskar
Kolberg (encoded in EsAC format in the IS PAN), and the analysis of a
corpus of polyphonic music made available by the pioneering The
Josquin Research Project. Students will also analyse selected texts
describing research using computer methods and repeat the analytical
procedures applied using Humdrum tools.
Type of course
Mode
Course coordinators
Learning outcomes
Students:
have a structured knowledge of the historical outline of
digital musicology,
are aware of the role of Polish scientific projects in shaping
the field,
are familiar with the main developments and the most
important music corpora and digital projects,
are familiar with the most important scientific research in
the field of musicology,
are able to recognise different music coding formats, are
familiar with analytical tools enabling their
application in research work,
are familiar with the basics of coding in Humdrum **kern
language,
are familiar with HumdrumTools and HumdrumExtras
analytical tools and are able to apply them in practice,
are able to combine theoretical and practical knowledge and
plan their own simple research projects using digital tools.
Assessment criteria
Activity and attendance at classes (two unexcused absences allowed,
the number of excused absences should not exceed 1/3 of the classes
Planning a research project using Humdrum digital tools (posing the
research question, planning the analytical steps, selecting the appropriate
commands, from the Humdrum toolkit, allowing the necessary
calculations to be made)
Bibliography
1. David Huron, “Lecture 3. Methodology: The New Empiricism:
Systematic Musicology in a Postmodern
Age,” in The 1999 Ernest Bloch Lectures, ed. David Huron (Berkeley:
University of California, 1999).
2. David Huron (1996). The Melodic Arch in Western Folksongs.
Computing in Musicology. 10.
3. Charles Inskip, and Frans Wiering, “In their own words: using text
analysis to identify musicologists'
attitudes towards technology” (paper presented at 16th International
Society for Music Information
Retrieval Conference, Malaga, Spain, October 26, 2015), 455-461.
4. Fabian C. Moss, “Transitions of Tonality: A Model-Based Corpus
Study” (PhD thesis, Lausanne,
Switzerland, 2019), Chapter III Mesoanalysis,
https://infoscience.epfl.ch/record/273178.
5. Nicolas Cook, and Craig Sapp, “Purely Coincidental? Joyce Hatto and
Chopin’s Mazurkas,” CHARM
Newsletter, May 2007,
https://charm.cch.kcl.ac.uk/redist/pdf/2007newsletter.pdf.
6. Vanessa Nina Borsan, Mathieu Giraud, Richard Groult. The Games
We Play: Exploring The Impact of
ISMIR on Musicology
7. International Society for Music Information Retrieval Conference
(ISMIR 2023), Nov 2023, Milano,
Italy. pp.474-481, ⟨10.5281/zenodo.10265344⟩
Additional information
Additional information (registration calendar, class conductors, localization and schedules of classes), might be available in the USOSweb system: