Volume 1, Issue 1, January 2011 - DROPS - Schloss Dagstuhl

Meinard Müller, Masataka Goto, and Simon Dixon 95
3.36 What is it Like to be a Musicologist?
Frans Wiering (Utrecht University, NL)
License Creative Commons BY-NC-ND 3.0 Unported license
© Frans Wiering
In this presentation, I investigated the relationship between present-day musicology and
computational music processing. These two fields seem to be far apart: computing has at
best a role as tool supplier in mainstream musicological research and musicology figures
mainly as a source of domain knowledge and ground truth in computational music processing.
Setting aside the matter of different methodologies, there seem to exist completely different
views as to what music is. One important reason why this is the case relates to the crisis
that took place in musicology in the late 1980s.
Before that time, musicology used to be first of all about Western classical music. Its
central concept was the musical “work,” the autonomous artistic creation exemplified by the
score that captured the composer’s intention. This “positivist” view of music was not so much
superseded as stripped of its credibility in the following decades of “critical” musicology. The
work concept itself was shown to be a cultural construction, loaded with prejudice against
other possible views of music. Critical musicology has today become mainstream musicology,
examining musical meaning, subjectivity, culture, context, gender and identity rather than
beauty, structure and indeed “the music itself.”
Music processing is first of all about music as data, whether notation, audio or otherwise.
Its benefits are the well-known ones of computation: size, speed, accuracy and formal
modelling, but the mismatch with musicology is obvious. However, a common ground may
be found in what David Huron has called a “new empiricist” approach. Studies of context,
subjectivity and meaning generation may benefit from data-rich approaches complementing
the anecdotic evidence that they generally are based on. For example, in meaning generation
high-level musical patterns shared between different pieces play an important role, but to
understand this role massive amounts of music need to be analysed.
3.37 What does it Mean to “Process” “Music”?
Geraint A. Wiggins (Goldsmiths, University of London, GB)
License Creative Commons BY-NC-ND 3.0 Unported license
© Geraint A. Wiggins
There is a significant gap (sometimes called a “semantic” gap, but that is only partly correct
in one particularly narrow usage of the word “semantic”) between the audio signal, which
corresponds with “Sound” in the air, and “Music” which is the experience that arises in
an appropriately enculturated human mind as a result of the application of an appropriate
audio stimulus. My research is about understanding “Music” from this viewpoint, and
identifying representations that properly model the human experience of music, and studying
their properties. This entails a certain amount of perceptual and cognitive psychology,
since, I claim, the word “Music” has no meaning except where a mind is involved. In this
my presentation, I tried to bridge the (non-semantic) gap between audio signals and the
human experience of music, via what are sometimes called symbolic, mid-level, or discrete
representations. While none of these names are incorrect, none of them captures the point:
to be meaningful, the representations need to be perceptually and/or cognitively valid.
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