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Details of Grant 

EPSRC Reference: GR/S84750/01
Title: Hierarchical Segmentation & Semantic Markup of Musical Signals
Principal Investigator: Casey, Professor M
Other Investigators:
Researcher Co-Investigators:
Project Partners:
Department: Computing Department
Organisation: Goldsmiths College
Scheme: Standard Research (Pre-FEC)
Starts: 01 June 2004 Ends: 31 August 2007 Value (£): 195,971
EPSRC Research Topic Classifications:
Digital Signal Processing Information & Knowledge Mgmt
Multimedia
EPSRC Industrial Sector Classifications:
Creative Industries
Related Grants:
GR/S84743/01
Panel History:  
Summary on Grant Application Form
The rapid introduction of peer-to-peer file sharing, MP3-compressed audio players and commercial music downloading services has created a demand for new research into automatic segmentation and classification of music signals. Technologies that perform reliably in this regard are required for media asset management for on-line music services, media archiving services and for consumer music devices. The aim of this research programme is to develop new signal processing algorithms that perform meaningful segmentations of musical signals for these applications. The proposed methods discover structural relationships between timbral events in audio signals; this will be a representation of the information content of the signal vis-a-vis human listening. Extraction of meaningful segments from music requires the development of new audio algorithms for information extraction that are oriented toward musical patterns as they are perceived by humans. In our framework, the higher-order structure in music, that gives it its meaning, is expressed over patterns of 'timbre textures' that consist of groups of individual instruments playing as an ensemble. By treating such aggregates as unit textural elements, the higher-order patterns in a piece of music can be extracted at many hierarchical levels such as beat, bar, phrase and movement.
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Organisation Website: http://www.gold.ac.uk