2010:Symbolic Music Similarity and Retrieval

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Description

Retrieve the most similar items from a collection of symbolic documents, given a query, and rank them by melodic similarity. The following tasks could be defined this year:

Task 1: Monophonic to monophonic. Both the query and the documents in the collection will be monophonic.

Task 2: Monophonic to polyphonic. The documents will be polyphonic (i.e. can have simultaneous notes), but the query will still be monophonic.

Task 3: Polyphonic to polyphonic. Both the query and documents will be polyphonic.

Task Specific Mailing List

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Data

  • 5,274 tunes belonging to the Essen folksong collection. The tunes are in standard MIDI file format. Download (< 1 MB)


Evaluation

The same method for building the ground truth as last year will be used. This method has the advantage that no ground truth needs to be built in advance. After the algorithms have been submitted, their results are pooled for every query, and human evaluators are asked to judge the relevance of the matches for some queries.

Submission Format

Input

Parameters:
- the name of a directory containing about 5,000 MIDI files containing monophonic folk songs and
- the name of one MIDI file containing a monophonic query.

The program will be called once for each query.

Expected output

A list of the names of the 10 most similar matching MIDI files, ordered by melodic similarity. Write the file name in separate lines, without empty lines in between.

Measures

Use the same measures as 2006:Symbolic_Melodic_Similarity_Results to compare the search results of the various algorithms.

Packaging submissions

All submissions should be statically linked to all libraries (the presence of dynamically linked libraries cannot be guarenteed).

All submissions should include a README file including the following the information:

  • Command line calling format for all executables and an example formatted set of commands
  • Number of threads/cores used or whether this should be specified on the command line
  • Expected memory footprint
  • Expected runtime
  • Any required environments (and versions), e.g. python, java, bash, matlab.