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Recent Research Projects
STOCHASTIC SCORE FOLLOWING
FOR VOCAL ACCOMPANIMENT
Automated accompaniment systems take a musical score as input, listen to live performers,
and
play the remaining parts of the score to provide synchronous, real-time
accompaniment. These
systems must track the live performers by determining their score position and tempo in
real-time.
Tracking a vocal performer has proved to be an extremely challenging problem. This
work focuses
on defining and implementing a statistical model for tracking vocal performers. The
model is based
upon observed properties of vocal performance. It uses a variety of information
including estimated
tempo, observed fundamental pitch, and observed spectral features that correlate
with speech.
The model has been fit to measurements taken from actual performances given by
vocal students.
Initial application of this model has demonstrated accompaniment ability that is
qualitatively superior
to previous vocal accompaniment systems. Current efforts focus on quantitatively
evaluating how
well the fitted model can track singers. Stochastic
Vocal Tracking (postscript)
COMPUTER PERFORMANCE WITHIN
A MUSICAL ENSEMBLE
Prior to this work, researchers had implemented several computer systems for accompanying
a solo performer. The system developed for this project performed as part of a live
ensemble, listening
to and accompanying multiple performers. Using previously developed tracking technology,
the system independently estimated score position and tempo of each performer in
the ensemble.
Individual estimates were then combined to estimate the ensemble score position and
tempo. These
estimates were used to control the computer performance. The completed system
performed works by
Handel and Mozart with ensembles having as many as four live musicians.
Ensemble Performance (postscript)
Related Research: See the Computer Music
Project at CMU.
Selected Publications
Grubb, L. and Dannenberg, R.B. 1997.
"A Stochastic Method of Tracking a Vocal Performer."
In Proceedings of the1997 International Computer Music Conference (ICMC-97),
301-308.
San Francisco: International Computer Music Association.
Grubb, L. and Dannenberg, R.B. 1995. (Video)
"Ensemble Accompaniment."
In Computer Music Video Review, 2(1).
San Francisco: International Computer Music Association (ICMA).
Grubb, L. and Dannenberg, R.B. 1994.
"Automating Ensemble Performance."
In Proceedings of the 1994 International Computer Music Conference (ICMC-94),
63-69.
San Francisco: International Computer Music Association (ICMA).
Grubb, L. and Dannenberg, R.B. 1994.
"Automated Accompaniment of Musical Ensembles."
In Proceedings of the Twelfth National Conference on Artificial Intelligence (AAAI-94),
94-99.
Cambridge, MA: MIT Press.
Grubb, L. and Dannenberg, R.B. 1994.
"Computer Performance in an Ensemble."
In Third International Conference for Music Perception and Cognition Proceedings,
57-60.
Liege, Belgium: European Society for the Cognitive Sciences of Music.
Grubb, L. 1992.
"Use of Computational Models in a Rule-Based Expert Decision System."
In Proceedings of the 1992 IAKE Symposium on Knowledge Engineering, 597-602.
Gaithersburg, MD: International Association of Knowledge Engineers (IAKE).
Grubb, L. 1992.
"Domain Independent Natural Language Processing and Automated Reasoning."
In Proceedings of the 1992 IAKE Symposium on Knowledge Engineering, pp. 754-765.
Gaithersburg, MD: International Association of Knowledge Engineers (IAKE).
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