Interacting with Digital Music

Abstract

It seems that every week there is a new Digital Music product and service and every week another major deal is announced. That is the intensively competitive Digital Music market today. For those of us lucky enough to work in Digital Music research, these are exciting times with almost boundless possibilities. These are made possible by recent advances in musical signal (or content) analysis, which is increasingly able to capture the underlying musical intent in a recording. Consequently, research communities around the world have been increasingly mobilized to respond to the research challenges that the market presents. This paper presents a view from the United Kingdom describing how we have become better organized, particularly by means of a research practitioners network called the Digital Music Research Network. It continues with an overview of some relevant research at one UK university, Queen Mary University of London, and then presents a personal view of how research practice might evolve in the future.

Acknowledgements

My thanks are due to the following members of the Centre for Digital Music whose work I have included in this paper: Mark Plumbley, Samer Abdallah, Juan Pablo Bello (now at New York University), Chris Landone, Mark Levy, Chris Sutton, Chris Cannam, Chris Harte, Katy Noland, Matthew Davies and Yves Raimond. Thanks are also due to collaborators at OFAI in Vienna: Gerhard Widmer, Elias Pampalk and Martin Gasser.

I would also like to thank the editors of this special issue, whose constructive comments have helped to improve this paper significantly.

I would also like to recognize the contributions to the work reported from the following grants: Object-based Coding of Musical Audio, EPSRC Grant GR/S75802/01; Advanced Subband Systems for Audio Source Separation, EPSRC Grant GR/S85900/01; Hierarchical Segmentation & Semantic Markup of Musical Signals, EPSRC Grant GR/S84743/01; Digital Music Research Network, EPSRC Grant GR/R64810/01; OMRAS2, EPSRC Grant GR/E017614/1; SIMAC, EU Grant FP6-IST-507142.

Notes

¹ http://www.musicontology.com

² http://www.sonicvisualiser.org/

³ http://sv.mazurka.org.uk/

⁴ http://en.wikipedia.org/wiki/Tonnetz

⁵musicbrainz.org

⁶MI is defined here as the study, extraction, representation and processing of information in music. It includes Music Information Retrieval, Semantic Audio, Symbolic Music processing, Intelligent Effects and intelligent creativity support systems for Composers and Producers.

⁷ http://dactyl.som.ohio-state.edu/Humdrum/

⁸ http://www.visualizationsoftware.com/gram.html

⁹ http://www.ieee-tcdl.org/Bulletin/v2n1/downie-1/downie-1.html