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| EPSRC Reference: |
GR/S82213/01 |
| Title: |
Techniques and Algorithms for Understanding the Information Dynamics of Music |
| Principal Investigator: |
Professor M Plumbley |
| Other Investigators: |
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| Researcher Co-investigator: |
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| Project Partner: |
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| Department: |
Sch of Electronic Eng & Computer Science |
| Organisation: |
Queen Mary, University of London |
| Scheme: |
Standard Research |
| Starts: |
01 May 2005 |
Ends: |
30 April 2008 |
Value (£): |
184,965
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| EPSRC Research Topic Classifications: |
| Information and Knowledge Management |
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| EPSRC Industrial Sector Classifications: |
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| Related Grants: |
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| Panel History: |
| Panel Date | Panel Name | Outcome |
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04 Feb 2004
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Computer Science Panel (Tech) 4 February 2004
|
Deferred
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Summary |
The aim of this project is to develop a novel data-driven methodology for automatically analysing the dynamic structure of music. The project will focus on the idea of expectation and surprise in music, and we will investigate how these can be quantified in terms of measures derived from information theory, related to the hypothesis of redundancy reduction in perception.
Combining the particular expertise of the two host groups, we will develop and evaluate a range of probabilistic models of music in the audio and symbolic domains, including hierarchical models crossing both domains. The output of models will be compared to current music theory, experimentally measured human responses to music, and to other computational methods for analysing musical structure. We expect that symbolic representations related to e.g. notes, events and tonal hierarchy will emerge from our analysis, though the outcome will not be pre-judged and may reveal subtleties not reflected in standard representations of music.
This is an adventurous proposal. We anticipate that this project will produce important new insights into the structure of music and other time-based sionals. and could gave the wav for significant future advances in music analvsis and Processing
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| Final Report Summary |
The aim of this project is to develop a novel data-driven methodology for automatically analysing the dynamic structure of music. The project will focus on the idea of expectation and surprise in music, and we will investigate how these can be quantified in terms of measures derived from information theory, related to the hypothesis of redundancy reduction in perception.
Combining the particular expertise of the two host groups, we will develop and evaluate a range of probabilistic models of music in the audio and symbolic domains, including hierarchical models crossing both domains. The output of models will be compared to current music theory, experimentally measured human responses to music, and to other computational methods for analysing musical structure. We expect that symbolic representations related to e.g. notes, events and tonal hierarchy will emerge from our analysis, though the outcome will not be pre-judged and may reveal subtleties not reflected in standard representations of music.
This is an adventurous proposal. We anticipate that this project will produce important new insights into the structure of music and other time-based sionals. and could pave the way for significant future advances in music analvsis and processing.
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| Further Information: |
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| Organisation Website: |
http://www.qmul.ac.uk |
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