COMPGC20 - Computer Music

Note: Whilst every effort is made to keep the syllabus and assessment records correct, the precise details must be checked with the lecturer(s).
Code
 COMPGC20 
Year
MSc
Prerequisites

The course has no formal prerequisites but involves programming in graphical and textual languages, and engagement with musical concepts. No prior knowledge of programming is assumed and the languages used are taught from first principles, however, those with no or very little  computing experience of any kind may find the learning curve quite steep! Thus some basic knowledge of programming in any language will be  helpful.  On the musical side, it will help if you have some basic knowledge of music but again, this can be learned from books and will be  briefly taught on the course if needed.  Reviewing this page <http://www.cs.cmu.edu/%7Emusic/cmsip/readings/music-theory.htm> may give some idea of the knowledge required.  Prospective students are encouraged to contact the lecturer <mailto:n.gold@ucl.ac.uk> to discuss their suitability.  See also: www0.cs.ucl.ac.uk/staff/N.Gold/teaching/&nbsp;

Term
2
Taught By
Nicolas Gold (100%) 
Aims
To provide students with a grounding in the state of the art in computer music theory, technology and applications. 
Learning Outcomes
Students successfully completing this module should be able to: 
  • demonstrate knowledge of key issues in contemporary computer music.
  • demonstrate a knowledge of ethical issues related to music intellectual property.
  • analyse problems in computer music analysis, representation, and creation.
  • synthesise solutions to such problems on the basis of contemporary tools and theories.
  • evaluate such solutions using appropriate methods
  • manage their own learning in terms of acquiring disciplinary knowledge from academic literature
  • evaluate their own solutions
  • work autonomously
  • solve complex problems
  • develop and apply software development skills in the production of software for creative tasks in the music domain.

Content:

The course will cover three key aspects of computer music: representation, creativity and analysis addressed through theory and practice. It will cover sound, music as organised sound, and specific applications (e.g. music information retrieval and musicology). Students will be strongly encouraged to explore both scientific and artistic aspects of the course through programming exercises to generate sound and music in contemporary visual or textual music and arts programming languages (e.g. Python, Javascript, Nyquist, Pure Data). Students will be expected to compose a short algorithmic work using the computer and the techniques taught and developed.

Indicative topics

Ethical Issues and Evaluation of Music Systems

Audio and Sampling

Synthesis

Introduction to Tonal Music Theory

Symbolic representations of music (MIDI, Kem, MusicXML)

Algorithmic Composition

Music Information Retrieval

Computational Musicology

Method of Instruction:

Lectures, laboratories, and demonstrations of techniques. Students will be given weekly  exercises to explore and practice techniques. Reading and listening recommendations will also be provided via Moodle.

Assessment:

The course has the following assessment components:

  • Unseen written examination (2 hours, 90%)
  • Algorithmic composition (audio file, programe notes, source code) (10%)

To pass the course students must:

  • Gain an overall mark of 50% or above

Resources:

Bibliography

General Topics

The Computer Music Tutorial, Curtis Roads, MIT Press, 1996. ISBN 0262680823.

Introduction to Computer Music, Nick Collins, Wiley, 2009, ISBN 978-0-470-71455-3.

Musimathics, vol. 1, Gareth Loy, MIT Press, 2006, ISBN 0262122820.

Musimathics, vol. 2, Gareth Loy, MIT Press, 2007, ISBN 0262122855.

Artistic and Historical Aspects

The Cambridge Companion to Electronic Music, Nick Collins & Julio d’Escrivan, Cambridge University Press, ISBN 9780521688659.

Computer Composition

Virtual Music, David Cope, MIT Press, 2001, ISBN 026203283X.

Computer Models of Musical Creativity, David Cope, MIT Press, 2006, ISBN 0262033380.

Machine Musicianship, Robert Rowe, MIT Press, 2004, ISBN 0262681498.

Algorithmic Composition, Mary Simoni & Roger Dannenberg, 2011, forthcoming (core text)

Algorithmic Composition: Paradigms of Automated Music Generation, Gerhard Nierhaus, Springer, 2009, ISBN 978-3-211-75539-6.

Analysis

Signal Processing Methods for Music Transcription, Anssi Klapuri & Manuel Davy (eds), Springer, 2006, ISBN 978-0-387-30667-4.

Music and Probablity, David Temperley, MIT Press, 2007, ISBN 0-262-20166-6.

The Cognition of Basic Musical Structures, David Temperley, MIT Press, 2002, ISBN 0262201348.

Representation

Beyond MIDI, Eleanor Selfridge-Field (ed), MIT Press, 1997, ISBN 0262193949.

MusicXML, http://www.recordare.com/musicxml

The HumDrum Toolkit, http://www.musiccog.ohio-state.edu/Humdrum/

Musicology

Musicology: The Key Concepts, David Beard & Kenneth Gloag, Routledge, 2005, ISBN 0415316928.

NyQuist Programming

NyQuist Reference Manual, Roger Dannenberg, http://www.cs.cmu.edu/~rbd/doc/nyquist/

(see also Algorithmic Composition, Simoni and Dannenberg above)

PureData Programming

Pure Data website, http://puredata.info

Pure Data, http://en.flossmanuals.net/PureData

Programming Electronic Music in Pd, Johannes Kreidler, Wolke Publishing, 2009, ISBN 3936000573.

Journal and conference papers will also be used to supplement these texts.