School of Electronic Engineering and Computer Science

Intelligent systems for audio production

Supervisor: Professor Josh Reiss

Research group(s): Centre for Digital Music

This PhD topic aims to intelligently generate an automatic sound mix out of an unknown set of multi-channel inputs. The research also explores the possibility of creating an intelligent system that ‘learns’ the mixing decisions of a skilled audio engineer with minimal or no human interaction. The input channels can be analysed to determine preferred settings for gain, equalization, compression, reverb, and so on. Alternatively, entirely new approaches to audio production can be taken, since an intelligent system is capable of far more analysis and manipulation than can be performed manually. This research has application to live music concerts, remote mixing, recording and postproduction as well as live mixing for interactive scenes.
The justification of this research is the need of non-expert audio operators and musicians to be able to achieve a quality mix with minimal effort. Currently, mixing is a task which requires great skills, practice and can be sometime tedious. For the professional mixing engineer this kind of tool will reduce sound check time and allow the engineer to focus on the creative aspects of production.
This research topic builds on previous, successful work by researchers within the Centre for Digital Music, but is broad enough in scope that it could be taken in new and exciting directions.