|
| EPSRC Reference: |
EP/E017614/1 |
| Title: |
OMRAS2: A Distributed Research Environment for Music Informatics and Computational Musicology |
| Principal Investigator: |
Professor M Sandler |
| Other Investigators: |
|
| Researcher Co-investigator: |
|
| Project Partner: |
| King's College London The Strand |
Lancaster University |
Matrix-Data Ltd |
| Royal Holloway, Univ of London |
University of Surrey |
|
|
| Department: |
Sch of Electronic Eng & Computer Science |
| Organisation: |
Queen Mary, University of London |
| Scheme: |
Standard Research |
| Starts: |
01 February 2007 |
Ends: |
31 October 2010 |
Value (£): |
1,447,587
|
| EPSRC Research Topic Classifications: |
| Multimedia |
User Interface Technologies |
|
| EPSRC Industrial Sector Classifications: |
|
| Related Grants: |
|
| Panel History: |
| Panel Date | Panel Name | Outcome |
|
07 Sep 2006
|
ICT Large Grants
|
Announced
|
|
|
Summary |
Imagine you have just bought a new iPod, you rip loads of your dad's CDs into it (his music's cool) as well as your own, and pretty soon you have 10,000 tracks and the iPod is full. Now there's a problem. You've never listened to your dad's CDs (not that many of them anyway) and you're really not sure what The Human League sounds like, and there's another 500 CDs of his music in there. Where are the good songs? How can you ever build those really cool playlists to impress your friends with your vast musical knowledge?
Online Music Recognition and Searching II A Distributed Framework for Music Informatics and Computational Musicology.
Imagine you've just been given a gist subscription to a 2 million song online music store. You can choose 10,000 songs to download onto your music player, but there's a problem. You have never heard a vast majority of these songs so you're not sure which are the one's you like. How can you put together those playlists to impress your friends with your vast musical knowledge?
The problem is simular for the radio DJ looking for a new playlist to keep their show on the cutting edge, or the professional violinist doing research into different performances of Vivaldi'd Four Seasons to find a new twist for an expectant audience, or the recors producer trying to find a mathimatical formula for number one singles (yes, they really do this).
The answer to the above question and other interesting problems concerning large collections of digital music are exactly what the OMRAS2 project will address. When OMRAS2 is completed, you'll be able to get software that helps you build playlists with songs that you'll love even though you never heard them before; and there will be tools to help the violinist and record producer achive their goals too. Using tools from OMRAS2, your ipod will be able to predict the best sounds to use for the best chart topping number one. If you study music at University, you'll probably use OMRAS2 for analysing and comparing music.
OMRAS2 aims to help technology researchers build and investigate the software that is needed to construct these super-tools. But that's not all. It will help musci researchers investigate interesting aspect of music, such as what variations of that riff in Purple Haze did Jimi Hendrix play and how did the differ, and how did different pianists interpret Bach's Goldberg Variations. OMRAS2 will also look deeply at how music and information about music (like CD Insert booklets, but more and online) will be enjoyed at home, not just downloading, but also searching, recomending, browsing and so on. And it wont be hard to use:
OMRAS2 will use interfaces that look and react like familiar music software like Adobe Audition or RealAudio player.
|
| Final Report Summary |
|
No final report summary is available for this grant.
|
| Further Information: |
|
| Organisation Website: |
http://www.qmul.ac.uk |
|
|