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

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

  • Towards Web-Scale Analysis of Musical Structure
    David De Roure
    J. Stephen Downie
    Kevin Page
    Ichiro Fujinaga
    Tim Crawford
    Ben Fields
    David Bretherton

    salami.music.mcgill.ca
  • SALAMI Objectives
    SALAMI == Structural Analysis of Large amounts of Music Information
    Musical analysis has traditionally been conducted by individuals and on a small scale
    Computational approach, combined with the huge volume of data now available, will
    Deliver substantive corpus of musical analyses in common framework for music scholarsand students
    Establish a methodology and tooling so that community can sustain and enhance this resource
    www.diggingintodata.org
  • Motivation
    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
    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
    It can also be used to understand historical influences over time and location
  • Digital Music Collections
    23,000 hours ofrecorded music
    Music InformationRetrieval Community
    Community Software
    Student-sourced ground truth
    Supercomputer
    Linked Data Repositories
  • Ground Truth
    Ashley Burgoyne
  • Number of annotated pieces by genre
  • Segment Ontology
    class structure
    Ontology models properties from musicological domain
    • Independent of Music Information Retrieval research and signal processing foundations
    • Maintains an accurate and complete description of relationships that link them
    Kevin Page and Ben Fields
  • See Kevin Pagefor more info…
  • MIREX Overview
    Stephen Downie
    Music Information Retrieval Evaluation eXchange
    Began in 2005
    Tasks defined by community debate
    Data sets collected and/or donated
    Participants submit code to IMIRSEL
    Code rarely works first try 
    Huge labour consumption getting programs to work
    Meet at ISMIR to discuss results
    www.music-ir.org/mirex
  • Meandre
    seasr.org/meandre
  • Structural analysis processing time by different algorithms
    Evaluations of 3 algorithms and human against a ground truth
    FPC = Frame Pair Clustering
  • It’s web-like!
    “Ground Truth”
    Community
    Digital Audio
    “Signal”
    StructuralAnalysis
  • How country is my country?
    Kevin Page and Ben Fields
    http://www.nema.ecs.soton.ac.uk/countrycountry/
  • Summary
    • Web-scale methodology to conduct analysis of music recordings to create resource for musicologists
    • Investigating algorithms for structural analysis
    • Answering new research questions, evolving new methodologies
    • For more info
    http://salami.music.mcgill.ca/
    http://www.oerc.ox.ac.uk/people/dder
    • Thanks to international teams, Internet Archive, Digging into Data Challenge, collaborators & funders