摘要：John Blacking said “The main task
of ethnomusicology is to explain music and
music making with reference to the social, but
in terms of the musical factors involved in
performance and appreciation” (1979:10). For
this reason, research in ethnomusicology has,
from the beginning, involved analysis of
sound, mostly in the form of transcriptions
done “by ear” by trained scholars. Bartók’s
many transcriptions of folk music of his native
Hungary are a notable example.
Since the days of Charles Seeger, there have
been many attempts to facilitate this analysis
using various technological tools. We survey
such existing work, outline some guidelines
for scholars interested in working in this area,
and describe some of our initial research efforts
in this field. We will use the term “Computational
Ethnomusicology” (CE) to refer to
the design, development and usage of computer
tools that have the potential to assist in
ethnomusicological research. Although not
new, CE is not an established term and existing
work is scattered among the different disciplines
involved.
As we quickly enter an era in which all
recorded media will be “online,” meaning that
it will be instantaneously available in digital
form anywhere in the world that has an Internet
connection, there is an unprecedented need
for navigational/analytical methods that were
entirely theoretical just a decade ago. This era
of instantaneously available, enormous collections
of music only intensifies the need for the
tools that fall under the CE rubric.
We will concentrate on the usefulness of a
relatively new area of research in music called
Music Information Retrieval (MIR). MIR is
about designing and building tools that help us organize, understand and search large collections
of music, and it is a field that has been
rapidly evolving over the past few years,
thanks in part to recent advances in computing
power and digital music distribution. It encompasses
a wide variety of ideas, algorithms,
tools, and systems that have been proposed to
handle the increasingly large and varied
amounts of musical data available digitally.
Researchers in this emerging field come from
many different backgrounds including computer
science, electrical engineering, library
and information science, music, and
psychology. The technology of MIR is ripe to
be integrated into the practice of
ethnomusicological research. To date, the
majority of existing work in MIR has focused
on either popular music with applications such
as music recommendation systems, or on
Western “classical” music with applications
such as score following and query-byhumming.
In addition, as microchips become smaller
and faster and as sensor technology and actuators
become cheaper and more precise, we
are beginning to see ethnomusicological research
incorporating both robotic systems and
digital capture of music-related bodily gestures;
music in general is embodied and involves
more than a microphone can record.
Our hope is that the material in this paper will
help motivate more interdisciplinary and multidisciplinary
researchers and scholars to explore
these possibilities and solidify the field
of computational ethnomusicology.
关键词：Ethnomusicology, music information
retrieval, automatic transcription, musical gesture,
human-computer interface, musical robotics
