These are some of the projects that are typical of research and
development in Music and Technology at Carnegie Mellon.
is a sound synthesis and composition language offering a Lisp syntax as
well as an imperative language syntax and a powerful integrated
Nyquist is an elegant and powerful system based on functional
free, open source software for recording and editing
sounds. It is available for Mac OS X, Microsoft Windows, GNU/Linux, and
other operating systems. Audacity was originally designed and developed
by Roger Dannenberg and Dominic Mazzoni working in Carnegie Mellon’s
School of Computer Science Computer Music Project.
AuraRT is a
software framework for creating interactive multimedia software,
particularly advanced interactive music compositions. A subproject is
AuraFX, a flexible signal processor configurable by end-users.
Popular Music Systems
This project studies interfaces and systems for performing popular
music using computers as highly autonomous music performers. Research
includes methods to synchronize with human performers, communication
between human and computer performers, high-quality sound synthesis,
score display and annotation, and automating audio effects.
is a robotic bagpipe player. It plays an ordinary
set of bagpipes using an air compressor to provide air and
electro-magnetic devices to power the "fingers" that open and close
tone holes that determine the musical pitch.
(Dawen Liang’s Thesis)
As the high-capacity data storage devices (e.g. portable hard drives, and USB flash drives) become available to everyone, musicians are able to record all of their rehearsals and save them digitally. Given large amount of unlabeled and unorga- nized rehearsal recordings, manually organizing them can be a huge task. Therefore, managing music audio databases for practicing musicians automatically is a new and interesting challenge.
This thesis describes a systematic investigation to provide useful capabilities to musicians both in rehearsal and when practicing alone. The goal is to allow musicians to automatically record, organize, and retrieve rehearsal (and other) audio to facilitate review and practice (for example, playing along with difficult passages). In order to accomplish this task, three separate problems should be solved:
Given the original recordings,extract the music segments and get rid of the non-music parts. A novel music classification system based on Eigenmusic and AdaBoost classifier to separate rehearsal recordings into segments is proposed.
Given the music segments from the previous step, the system should be able to group the segments which belong to the same composition together. An unsu- pervised clustering and alignment process to organize segments is introduced.
Finally, an interactive user interface is required for musicians to easily access and compare the previous rehearsals. The thesis provides a digital music display interface that provides both graphical input and output in terms of conventional music notation.
The thesis will address each of these 3 problems and provide an implementation that works in practice. Some future work is also described.
(Jiuqiang Tang’s Thesis)
During a music performance, a violinist, trumpeter, conductor and many
other musicians must actively use both hands. This makes it impossible to
also interact with a computer by pressing buttons or moving
faders. Musicians must often rely on offstage sound engineers and other
staff acting on a predetermined schedule. However, it seems that some
“natural” gestures, such as nodding the head or pointing, offer an
alternative way to help musicians control the output sounds in the
The goal of my work is to create an interactive music system able to spot
and recognize “command” gestures from musicians in real time. These
gestures trigger new sound events and control the output sounds. The system
allows the musician greater control over the sound heard by the audience
and the flexibility to make changes during the performance itself. In my
thesis, I design and evaluate a gesture recognition strategy especially for
music performance, based on the dynamic time warping algorithm and using an
F-measure evaluation process to obtain the best feature and threshold
combination. The proposed strategy will select features by searching over
all feature combinations, obtain the optimal threshold for each gesture
pattern of each feature combination in terms of the F-measure, and
automatically generate a gesture recognizer.
demonstration: Extracting Commands from Continuous Gestures
(Zeyu Jin’s Thesis)
Music notation includes a specification of control flow, which governs
the order in which the score is read using constructs such as repeats and
endings. Music theory provides only an informal description of control
flow notation and its interpretation, but interactive music systems
need unambiguous models of the relationships between the static score and
its performance. In this work, a framework is introduced to describe
music control flow semantics using theories of formal languages and
compilers. A formalization of control flow answers several critical
questions: Are the control flow indications in a score valid? What do the
control flow indications mean? What is the mapping from performance
location to static score location? The framework can be used to describe
extended control flow notation beyond conventional practice, especially
nested repeats and arrangement. With the introduction of SDL, the Score
Description Language, and DCL, the Dynamic Control Language, the
framework can be extended to describe scores notated with word
instructions and real-time controls. To demonstrate the correctness and
effectiveness of this framework, a score compiler and a score model
manager are implemented and evaluated using case-based tests. A
software, Live Score Display, is built upon this framework and is offered
as a component for interactive music display.
Live Score Display
website on SourceForge.
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