Department of Computer Science and Technology

Course pages 2018–19

Digital Signal Processing with Computer Music

Principal lecturers: Prof Alan Blackwell, Dr Markus Kuhn
Taken by: Part II CST 75%

No. of lectures and practical classes: 8 (plus 8 from DSP)
Prerequisite courses: Part 1 of Digital Signal Processing.
Capacity: no restrictions


This aim of this course is an introduction to computer music, including applications in generative composition, audio interaction, sonification, game sound and other non-speech audio. The basic principles of music information retrieval and musicological corpus analysis will be covered. Finally, the course will conclude with an overview of current research topics as addressed at venues such as NIME, ICLC, ICCM.


Part 1: Digital signal processing (Lecturer: Dr M. Kuhn)

Lectures 1-8 of the DSP course. This course teaches the basic signal-processing principles necessary to understand many modern high-tech systems, with audio, voice and communication examples. Students will gain practical experience from numerical experiments in MATLAB-based programming assignments.

Part 2: Computer music (Lecturer: Professor A. Blackwell)

  • Perception: pitch (chroma, temperament), timbre, rhythmic entrainment, spatialisation
  • Synthesis methods: sampling, wavetable, FM, granular synthesis, physical modelling
  • Machine listening: contemporary approaches to source separation, beat tracking, pitch estimation, transcription
  • Engineering: Audio processing tools and architectures, incl DAWs, UGens, SuperCollider
  • Musicological analysis: sound objects, pitch and harmony, structure, orchestration, genre and ethnomusicology
  • Audio interfaces: Sonification, audio display and non-speech audio interaction, new interfaces for music interaction
  • Composition: Algorithmic composition, generative music, game soundtracks, and live programming
  • Student-led session: research reviews, performance outlines


By the end of the course students should:

  • Understand the application of digital signal processing methods to the production of structured sounds;
  • Be able to apply principles of human perception and interaction to simple musical and non-speech audio applications.