Doi: 10.1145/1897852.1897874
technical Perspective
concerto for Violin
and Markov Model
By Juan Bello, Yann LeCun, and Robert Rowe
in the OPening moments of Jean Sibelius’ Violin Concerto, the young soloist
plays delicately, almost languidly. The
orchestra responds in kind, muting
the repeated string motif to a whisper.
As the piece progresses, soloist and orchestra alternatively perform the main
motifs in increasing measures of power and virtuosity, which inexorably lead
toward the movement’s stirring resolution. The soloist looks relieved as she
crosses the stage to shake the conductor’s hand.
This violinist, like most others in
music education, can benefit enormously from interacting with large
ensembles in honing her performing
skills. However, the demand far exceeds the number and capabilities of
existing orchestras, ensuring most of
these students won’t have access to this
experience. Our soloist is no exception.
The previous paragraph describes her
interaction with Chris Raphael’s Music
Plus One system: A machine learning-driven alternative to working with orchestras that retains much of the expressivity and interactivity that makes
concerto performance such a rewarding and educational experience. The
following paper details the approach,
for videos see http://www.music.infor-
matics.indiana.edu/papers/icml10/.
Automatic music accompaniment
has been actively researched since the
1980s, starting with the work of such pi-
oneers as Barry Vercoe and Roger Dan-
nenberg. The problem can be broken
into three subparts: 1 tracking the play-
ing of a human soloist, matching it to a
known musical score, and synthesizing
an appropriate accompaniment to that
solo part in real time. Solutions usually
involve ingenious pattern-matching
mechanisms for dealing with expres-
sive, incorrectly played or missing notes
in the soloist performance, while using
the output of the pattern match to drive
the scheduling of accompaniment
events. However, as Raphael notes, it is
impossible to accomplish score follow-
ing by reaction alone. The system must
incorporate a predictive component
that attempts to align upcoming notes
of the accompaniment with imminent
attacks of the human player. Failing to
solve this problem can result in poten-
tially disastrous consequences for the
performance.
Reference
1. Dannenberg, r.b. an on-line algorithm for real-time
accompaniment. In Proceedings of the International
Computer Music Conference (Paris, France, 1984),
193−198.
Juan Bello is an assistant professor of music technology
in the Department of music and Performing arts
Professions at nyu’s steinhardt school of Culture,
education and human Development.
Yann LeCun is silver Professor of Computer science and
neural science at nyu and co-founder of museami, a
music technology company.
Robert Rowe is a professor and vice chair in the Department
of music and Performing arts Professions at nyu’s steinhardt
school of Culture, education and human Development,
where he directs the music Composition Program.
© 2011 aCm 0001-0782/11/0300 $10.00