DHOxSS Digital Musicology

Abstract

A wealth of music and music-related information is now available digitally, offering tantalizing possibilities for digital musicologies. These resources include large collections of audio and scores, bibliographic and biographic data, and performance ephemera -- not to mention the 'hidden' existence of these in other digital content. With such large and wide ranging opportunities come new challenges in methods, principally in adapting technological solutions to assist musicologists in identifying, studying, and disseminating scholarly insights from amongst this 'data deluge'.

This workshop provides an introduction to computational and informatics methods that can be, and have been, successfully applied to musicology. Many of these techniques have their foundations in computer science, library and information science, mathematics and most recently Music Information Retrieval (MIR); sessions are delivered by expert practitioners from these fields and presented in the context of their collaborations with musicologists, and by musicologists relating their experiences of these multidisciplinary investigations.

The workshop comprises of a series of lectures and hands-on sessions, supplemented with reports from musicology research exemplars. Theoretical lectures are paired with practical sessions in which attendees are guided through their own exploration of the topics and tools covered. Laptops will be loaned to attendees with the appropriate specialised software installed and preconfigured.

Timetable

Time Title Speakers
Mon 3 July
11:00 - 11:15 Overview of Digital Musicology Workshop Kevin Page
11:15 - 11:30 Roundtable introduction from attendees Chair: Kevin Page
11:30 - 12:00 Digital Musicology: a personal perspective David Lewis
12:00 - 12:30 An Introduction to Music Information Retrieval: musicological implications J. Stephen Downie
14:00 - 16:00 Hands on: Using computers to analyse recordings: An introduction to signal processing David Weigl, Stephen Downie and Chris Cannam
16:30 - 17:00 Using computers to analyse recordings (contd.)
17:00 - 17:30 Using computer analyses to index and find recordings David Lewis
Tue 5 July
11:00 - 11:45 Historical musicology and digital cataloguing: achievements and possibilities Joana Bullivant
11:45 - 12:30 Authorial Fingerprinting for Renaissance Polyphony: Finding Contrapuntal Formulas in Two Corpora of French Chansons Catherine Motuz
14:00 - 16:00 Training computers automatically to recognise patterns in recordings (with handout) David Weigl and J. Stephen Downie
16:30 - 17:30 Methods for analysing large-scale resources and big music data Tillman Weyde
Wed 6 July
11:00 - 12:30 Annotating and structuring musicological knowledge on the Web using Linked Data Kevin Page
14:00 - 16:00 Digitised Notated Music: hands on with MEI David Lewis, Andrew Hankinson and David M. Weigl
16:30 - 17:30 Symbolic music analysis of renaissance counterpoint: current challenges Frauke Jurgensen
Thu 7 July
11:00 - 12:30 Automatic transcription of scnned notation: state of the art and applications. Hands on with Gamera Andrew Hankinson
14:00 - 14:30 An overview of software and data management best practice David Weigl
14:30 - 16:00 Computer processing of digital notated music: hands on with music21 (includes an introduction to programming in Python) David Lewis and David M. Weigl
16:30 - 17:30 Hands on with music21 (contd.)
Fri 8 July
11:00 - 12:30 A case study in Early Music: From digitisation to musicological research Tim Crawford
14:00 - 16:00 Hands on: from digitisation to analysis, an end-to-end example Tim Crawford, David Lewis, Andrew Hankinson, David Weigl, Kevin Page
16:30 - 17:30 Round table discussion: applied digital musicology in your research Everyone

Resources

Web pages

Software

The hands-on sessions of the workshop made use of a variety of software which was supplied to the students on specially customised laptops. All of the software used is free software and is also available free of charge online.

Sonic Visualiser
Vamp plugins
Tony (tool for melodic transcription)
MuseScore
Python
  • https://www.python.org/
  • Several of the tools used require Python
  • We used version 3.5
  • Python comes pre-installed with Mac OS
  • For Windows, see the download page
Jupyter (formerly IPython)
music21