Difference between revisions of "2010:Symbolic Music Similarity and Retrieval"
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| − | Retrieve the most similar items from a collection of symbolic documents, given a query, and rank them by melodic similarity. | + | 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 [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: | |
| + | |||
| + | * 0. No errors | ||
| + | * 1. One note deleted | ||
| + | * 2. One note inserted | ||
| + | * 3. One interval enlarged | ||
| + | * 4. One interval compressed | ||
| − | |||
| − | |||
=== Task Specific Mailing List === | === Task Specific Mailing List === | ||
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== Data == | == Data == | ||
| − | |||
* 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) | * 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) | ||
| − | + | * [http://www.essaymill.com termpapers] | |
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| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | |||
| − | [http://www. | ||
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==Evaluation == | ==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 == | == Submission Format == | ||
| − | + | '''Input''' | |
| − | + | Parameters:<br/> | |
| − | + | - the name of a directory containing about 5,000 MIDI files containing monophonic folk songs and <br/> | |
| − | Parameters: | + | - 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). [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). | |
| − | All submissions should be statically linked to all libraries (the presence of | + | * Be sure to follow the [[2006:Best Coding Practices for MIREX | Best Coding Practices for MIREX]] |
| − | dynamically linked libraries cannot be | + | * Be sure to follow the [[MIREX 2010 Submission Instructions]] |
| − | All submissions should include a README file including the following the | + | All submissions should include a README file including the following the information: |
| − | information: | ||
| − | * Command line calling format for all executables | + | * 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), | + | * 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 15:25, 16 December 2010
Contents
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
