Difference between revisions of "2010:Symbolic Music Similarity and Retrieval"

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== Task suggestion: Symbolic Melodic Similarity ==
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== Description ==
  
=== Description ===
 
  
Given a query, each system is supposed to return 10 most melodically similar songs from a given collection.
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Retrieve the most similar items from a collection of symbolic documents, given a query, and rank them by melodic similarity. There will be only 1 task this year.
 +
Monophonic to monophonic. Both the query and the documents in the collection will be monophonic.
  
1. Retrieve the most similar incipits from the UK subset of the RISM A/II collection (about 15,000 incipits), given one of the incipits as a query, and rank them by melodic similarity. Both the query and the collection are monophonic. Half the queries are hummed or whistled queries that have been converted to MIDI, thus with slight rhythmic and pitch imperfections, and half the queries are quantized in pitch and rhythm.
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Each system will be  given a query and returned the 10 most melodically similar songs from those taken from the Essen Collection (5274 pieces in the MIDI format; see [http://www.esac-data.org/ ESAC Data Homepage] for more information). For of the 6 queries, we made four classes of error-mutations, thus the set comprises the following query classes:
  
2. Like task 1, but with two collections of mostly polyphonic MIDI files to be searched for matches.The songs are are long in duration. The queries would still be monophonic. The first collection would be 10,000 randomly picked MIDI files from a collection of about 60,000 MIDI files that were harvested from the Web. They include different genres (Western and Asian popular music, classical music, ringtones, just to name a few). The second collection would be more focused: about 1000 .kar files (Karaoke MIDI files) with mostly Western popular music which stem from the same web harvest.
+
* 0. No errors
 +
* 1. One note deleted
 +
* 2. One note inserted
 +
* 3. One interval enlarged
 +
* 4. One interval compressed
 +
 
 +
 
 +
 
 +
=== Task Specific Mailing List ===
 +
You can <span class="plainlinks">[https://mail.lis.uiuc.edu/mailman/listinfo/mrx-com02 subscribe]</span> to this list to participate in the discussion.
  
 
== Data ==
 
== Data ==
  
3 different datasets are used for 3 subtasks.
 
  
*RISM: monophonic; 10,000 short files
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* 5,274 tunes belonging to the Essen folksong collection. The tunes are in standard MIDI file format. [http://www.ldc.usb.ve/~cgomez/essen.tar.gz Download] (< 1 MB)
*Karoke polyphonic; 1,000 long files.
 
*Mixed polyphonic; 15,741 long files.
 
  
All in MIDI format.
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* [http://www.essaymill.com termpapers]
  
 
==Evaluation ==
 
==Evaluation ==
=== Human Evaluation ===
 
The primary evaluation will involve subjective judgments by human evaluators of the retrieved sets using IMIRSEL's Evalutron 6000 system.
 
  
* Evaluator question: Given a search based on track A, the following set of results was returned by all systems. Please place each returned track into one of three classes (not similar, somewhat similar, very similar) and provide an inidcation on a continuous scale of 0 - 10 of high similar the track is to the query.
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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.
* 6/5/6 queries for RISM/Karaoke/Mixed datasets, 10 results per query, 1 set of eyes, ~10 participating labs
 
* Higher number of queries preferred as IR research indicates variance is in queries
 
* It will be possible for researchers to use this data for other types of system comparisons after MIREX 2007 results have been finalized.
 
* Human evaluation to be designed and led by IMIRSEL following a similar format to that used at MIREX 2006
 
* Human evaluators will be drawn from the participating labs (and any volunteers from IMIRSEL or on the MIREX lists)
 
  
 +
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 ==  
 
== Submission Format ==  
  
  
=== Inputs/Outputs ===
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'''Input'''
Input:
 
Parameters:
 
* the name of a directory containing the MIDI files
 
* the name of one MIDI file containing a monophonic query.
 
  
The program will be called 6 times. Three of the queries are going to be quantized (produced from symbolic notation) and three produced by humming or whistling, thus with slight rhythmic and pitch deviations.
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Parameters:<br/>
 +
- the name of a directory containing about 5,000 MIDI files containing monophonic folk songs and <br/>
 +
- the name of one MIDI file containing a monophonic query.
  
Output:
+
E.g.
- 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.
+
myAlgo.sh /path/to/folder/withMIDIfile/ /path/to/query.mid
  
=== Measures ===
 
Use the same measures as [[2006:Symbolic_Melodic_Similarity_Results]] to compare the search results of the various algorithms.
 
  
 +
 +
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 ===
 
=== 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  
+
* All submissions should be statically linked to all libraries (the presence of dynamically linked libraries cannot be guaranteed). [mailto:mirproject@lists.lis.uiuc.edu 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).
information:
+
* Be sure to follow the [[2006:Best Coding Practices for MIREX | Best Coding Practices for MIREX]]
 +
* Be sure to follow the [[MIREX 2010 Submission Instructions]]
  
* Command line calling format for all executables and an example formatted set of commands
+
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
 
* Number of threads/cores used or whether this should be specified on the command line
 
* Expected memory footprint
 
* Expected memory footprint
 
* Expected runtime
 
* Expected runtime
* Any required environments (and versions), e.g. python, java, bash, matlab.
+
* 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

Latest revision as of 16:25, 16 December 2010

Description

Retrieve the most similar items from a collection of symbolic documents, given a query, and rank them by melodic similarity. There will be only 1 task this year. Monophonic to monophonic. Both the query and the documents in the collection will be monophonic.

Each system will be given a query and returned 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 of the 6 queries, we made four classes of error-mutations, thus the set comprises the following query classes:

  • 0. No errors
  • 1. One note deleted
  • 2. One note inserted
  • 3. One interval enlarged
  • 4. One interval compressed


Task Specific Mailing List

You can subscribe to this list to participate in the discussion.

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