J. S. Downie, D. De Roure, K. Page.Towards Web-Scale Analysis of Musical Structure

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J. Stephen Downie (Graduate School of Library and Information Science, University of Illinois at Urbana-Champaign), David De Roure (Oxford e-Research Centre, University of Oxford) and Kevin Page (Oxford e-Research Centre, University of Oxford).
Music Linked Data Workshop, 12 May 2011, JISC, London.

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J. S. Downie, D. De Roure, K. Page.Towards Web-Scale Analysis of Musical Structure

  1. 1. Towards Web-Scale Analysis of Musical Structure<br />David De Roure<br />J. Stephen Downie<br />Kevin Page<br />Ichiro Fujinaga<br />Tim Crawford<br />Ben Fields<br />David Bretherton<br />…<br />salami.music.mcgill.ca<br />
  2. 2. SALAMI Objectives<br />SALAMI == Structural Analysis of Large amounts of Music Information<br />Musical analysis has traditionally been conducted by individuals and on a small scale<br />Computational approach, combined with the huge volume of data now available, will <br />Deliver substantive corpus of musical analyses in common framework for music scholarsand students<br />Establish a methodology and tooling so that community can sustain and enhance this resource<br />www.diggingintodata.org<br />
  3. 3. Motivation<br />A resource of this size empowers musicologists to approach their work in a new and different way, starting with the data, and to ask research questions that have not been possible before<br />The analysis is useful in classifying different genres of music and can be used to compare different styles of composition within a composer’s works or between composers<br />It can also be used to understand historical influences over time and location<br />
  4. 4. Digital Music Collections<br />23,000 hours ofrecorded music<br />Music InformationRetrieval Community<br />Community Software<br />Student-sourced ground truth<br />Supercomputer<br />Linked Data Repositories<br />
  5. 5. Ground Truth<br />Ashley Burgoyne<br />
  6. 6. Number of annotated pieces by genre<br />
  7. 7. Segment Ontology<br />class structure<br />Ontology models properties from musicological domain<br /><ul><li>Independent of Music Information Retrieval research and signal processing foundations
  8. 8. Maintains an accurate and complete description of relationships that link them</li></ul>Kevin Page and Ben Fields<br />
  9. 9. See Kevin Pagefor more info…<br />
  10. 10. MIREX Overview<br />Stephen Downie<br />Music Information Retrieval Evaluation eXchange<br />Began in 2005<br />Tasks defined by community debate<br />Data sets collected and/or donated<br />Participants submit code to IMIRSEL<br />Code rarely works first try <br />Huge labour consumption getting programs to work<br />Meet at ISMIR to discuss results<br />www.music-ir.org/mirex<br />
  11. 11.
  12. 12. Meandre<br />seasr.org/meandre<br />
  13. 13. Structural analysis processing time by different algorithms<br />Evaluations of 3 algorithms and human against a ground truth<br />FPC = Frame Pair Clustering<br />
  14. 14. It’s web-like!<br />“Ground Truth”<br />Community<br />Digital Audio<br />“Signal”<br />StructuralAnalysis<br />
  15. 15. How country is my country?<br />Kevin Page and Ben Fields<br />http://www.nema.ecs.soton.ac.uk/countrycountry/<br />
  16. 16.
  17. 17. Summary<br /><ul><li>Web-scale methodology to conduct analysis of music recordings to create resource for musicologists
  18. 18. Investigating algorithms for structural analysis
  19. 19. Answering new research questions, evolving new methodologies
  20. 20. For more info</li></ul>http://salami.music.mcgill.ca/<br />http://www.oerc.ox.ac.uk/people/dder<br /><ul><li>Thanks to international teams, Internet Archive, Digging into Data Challenge, collaborators & funders</li>

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