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Details of Grant 

EPSRC Reference: EP/L019981/1
Title: Fusing Semantic and Audio Technologies for Intelligent Music Production and Consumption
Principal Investigator: Sandler, Professor M
Other Investigators:
Reiss, Professor JD De Roure, Professor D Wiggins, Professor GA
Benford, Professor S
Researcher Co-Investigators:
Project Partners:
BBC Friedrich-Alexander Univ of Erlangen FAU Internet Archive
Microsoft Omnifone
Department: Sch of Electronic Eng & Computer Science
Organisation: Queen Mary University of London
Scheme: Programme Grants
Starts: 16 June 2014 Ends: 31 December 2019 Value (£): 5,199,944
EPSRC Research Topic Classifications:
Digital Signal Processing Human-Computer Interactions
Information & Knowledge Mgmt Music & Acoustic Technology
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
Panel History:
Panel DatePanel NameOutcome
12 Mar 2014 Programme Grant Interviews (ICT) - 12 March 2014 Announced
Summary on Grant Application Form
Music is probably the most pervasive of the performing arts, and perhaps, the most abused (think of your recent shopping trips!). It has tremendous power to influence our emotions, often subliminally. The advent of recording in the 19th Century made it possible to enjoy music at a time, and in a place, different from the performance. Compression, broadband and the ever increasing capacity to aggregate large collections mean that the issues confronting music consumers have totally changed in nature: equally so for professionals, such as broadcasters (playlists for radio, music for documentaries, etc.) and those at the creative heart of the process: musicians, sound engineers and producers. The recorded music industry has grappled unsuccessfully with digital technology and the rate of adoption of new technologies has been slow, ironically, mostly in fear of piracy and loss of revenue. Given the social and economic importance of music, it is vital that the industry's crisis is averted and its decline reversed. Simple semantics and metadata are already helping (for example in recommendation and sharing services) but this is just the beginning. The next generation semantic technologies that are the focus of this proposal have the power to exact the turnaround that music (and other content industries) needs but this should be established via a fundamental and principled exploration of how semantic technologies underpin music throughout the value chain.

The proposal brings the very latest technologies to bear on the complete industry, end-to-end, producer to consumer, making the production process more fruitful, the consumption process more engaging, and the delivery and intermediation more automated and robust. In this project we will address 3 premises: (i) that Semantic Web technologies should be deployed throughout the content value chain from producer to consumer; (ii) that advanced signal processing should be employed in the content production phases to extract "pure" features of perceptual significance and represent these in standard vocabularies; (iii) that this combination of semantic technologies and content-derived metadata leads to advantages (and new products and services) at many points in the value chain, from recording studio to end-user (listener) devices and applications.

The project will work with partners from industry - BBC R&D, Microsoft Research Cambridge and Omnifone) as well as internationally - the International Audio Labs, a joint initiative of the Fraunhofer Institute in Erlangan and the local university, and the Internet Archive, one of the world's major on-line libraries. We will engage with other universities in the UK supported by a partnership fund and via the BBC Audio Research Partnership.

This long term project will foster new ways for professionals to work with music in the studio and for consumers to engage in their homes. It will support new business models that emphasise the whole experience of musical involvement, and discover ways to monetise the metadata as well as the essential content. The technologies to be researched support new ways of learning (about and to play) music as well as new ways of teaching and performing. And because the project will encompass vast quantities of music data and metadata, from heterogeneous sources, and will stress test emerging principles of big data, distributed intelligence and future generation web, it also addresses key questions of wide significance to EPSRC's ICT Programme, particularly relating to Intelligent Information Systems and Working Together.

Key Findings
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