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SALAMI (Structural Analysis of Large Amounts of Music Information) is an ambitious computational musicology project which applies a computational approach to the huge volume of digital recordings now available from such sources as the Internet Archive. It aims to deliver a very substantive corpus of musical analyses in a common framework for use by music scholars, students and beyond, and to establish a web-based methodology and tooling which will enable others to add to this in the future. In its first phase the project has conducted a significant exercise in ground truth collection with 1000 recordings analysed by music students and shortly to be published as open Linked Data.
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Towards Web-Scale Analysis of Musical Structure
David De RoureJ. Stephen DownieKevin Page
salami.music.mcgill.ca
Ichiro FujinagaTim CrawfordBen FieldsDavid Bretherton…
• 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 1. Deliver substantive corpus of musical analyses in
common framework for music scholars and students2. Establish a methodology and tooling so that
community can sustain and enhance this resource
SALAMI Objectives
www.diggingintodata.org
• 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
Motivation
Digital Music Collections
Student-sourced ground truth
Community Software
Linked Data Repositories
Supercomputer
23,000 hours ofrecorded music
Music InformationRetrieval Community
Ashley Burgoyne
Ground Truth
Number of annotated pieces by genre
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
Segment Ontology
Kevin Page and Ben Fields
See Kevin Pagefor more info…
• 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
Stephen Downie
www.music-ir.org/mirex
MIREX Overview
seasr.org/meandreMeandre
Structural analysis processing time by different algorithms
Evaluations of 3 algorithms and human against a ground truthFPC = Frame Pair Clustering
“Signal”Digital Audio
“Ground Truth”
Community
It’s web-like!
StructuralAnalysis
How country is my country?
Kevin Page and Ben Fieldshttp://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
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