2010:Symbolic Melodic Similarity

Description

The goal of SMS is to retrieve the most similar items from a collection of symbolic pieces, given a symbolic query, and rank them by melodic similarity. There will be only 1 task this year, comprising a set of six "base" monophonic queries to be matched against monophonic a monophonic collection.

Each system will be given a query and is asked to return the 10 most melodically similar songs from those taken from the Essen Collection (5274 pieces in the MIDI format; see ESAC Data Homepage for more information). For each of the six "base" queries, we have created four classes of error-mutations, thus the query set comprises the following query classes:

• 0. No errors (i.e., "base")
• 1. One note deleted
• 2. One note inserted
• 3. One interval enlarged
• 4. One interval compressed

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 in the previous iterations in 2006 and 2007 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.

For each query (and its 4 mutations), the returned results (candidates) from all systems will then grouped together (query set) for evaluation by the human graders. The graders will provide with only heard perfect version against which to evaluate the candidates and did not know whether the candidates came from a perfect or mutated query. Each query/candidate set was evaluated by 1 individual grader. Using the Evalutron 6000 system, the graders gave each query/candidate pair two types of scores. Graders will be asked to provide 1 categorical score with 3 categories: NS,SS,VS as explained below, and one fine score (in the range from 0 to 10).

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.

E.g.

myAlgo.sh /path/to/folder/withMIDIfile/ /path/to/query.mid

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.

E.g.

query1.mid song242.mid song213.mid song1242.mid ...
query2.mid song5454.mid song423.mid song454.mid ...

...

E.g.

query1.mid,song242.mid,song213.mid,song1242.mid ...
query2.mid,song5454.mid,song423.mid,song454.mid ...

...

Packaging submissions

• All submissions should be statically linked to all libraries (the presence of dynamically linked libraries cannot be guaranteed). IMIRSEL should be notified of any dependencies that you cannot include with your submission at the earliest opportunity (in order to give them time to satisfy the dependency).
• Be sure to follow the Best Coding Practices for MIREX
• Be sure to follow the MIREX 2010 Submission Instructions

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

• Command line calling format for all executables including examples
• Number of threads/cores used or whether this should be specified on the command line
• Expected memory footprint
• Expected runtime
• Approximately how much scratch disk space will the submission need to store any feature/cache files?
• Any required environments/architectures (and versions) such as Matlab, Java, Python, Bash, Ruby etc.
• Any special notice regarding to running your algorithm

Note that the information that you place in the README file is extremely important in ensuring that your submission is evaluated properly.

Time and hardware limits

Due to the potentially high number of participants in this and other audio tasks, hard limits on the runtime of submissions will be imposed.

A hard limit of 24 hours will be imposed on feature extraction times.

A hard limit of 48 hours will be imposed on the 3 training/classification cycles, leading to a total runtime limit of 72 hours for each submission.

Submission opening date

TBA

Submission closing date

TBA