Difference between revisions of "2005:Symbolic Genre Class"

From MIREX Wiki
 
Line 46: Line 46:
 
* On-line repositories of MIDI files (sample links available at www.music.mcgill.ca/~cmckay/midi.html)
 
* On-line repositories of MIDI files (sample links available at www.music.mcgill.ca/~cmckay/midi.html)
 
* Research databases.
 
* Research databases.
 +
 +
==Review 1==
  
  

Revision as of 15:42, 1 February 2005

Proposer

Cory McKay (McGill University) cory.mckay@mail.mcgill.ca


Title

Genre Classification of MIDI Files


Description

Submitted software will automatically classify MIDI recordings into genre categories.

1) Genre Categories The genre categories will be organized hierarchically, in order to enable evaluation of how well entries can perform both coarse and fine classifications. The particular categories to be used will be determined by the evaluation committee. Individual recordings could belong to more than one category, as this is more realistic than requiring that each recording be classified as belonging to exactly one category. A total of three to five coarse categories and ten to fifteen fine categories will be used. Model classifications will be made by the evaluation committee or a sub-committee of the evaluation committee. Entrants will be provided with the selection and organization of categories so that they can configure their software to reflect them before submission.

2) Training and Testing Recordings Training and testing recordings will be chosen by the evaluation committee and kept confidential until after evaluations are complete. The test recordings will then be released, copyrights permitting.

3) Input Data Training will be performed by providing the software (through a command-line argument) with a text file listing training MIDI file paths and model genre(s). Testing will be performed by providing the software (through a command-line argument) with a text file that contains a list of file paths of test MIDI recordings.

4) Output Data The software will produce a text file listing test recording file paths and the genre(s) that each has been classified as.


Potential Participants

  • George Tzanetakis (University of Victoria), gtzan@cs.uvic.ca, high likelihood
  • Cory McKay & Ichiro Fujinaga (McGill University), cory.mckay@mail.mcgill.ca, high likelihood
  • Pedro J. Ponce de Leon & Jose M. Inesta (Universidad de Alicante), pierre@dlsi.ua.es, medium likelihood
  • Roberto Basili, Alfredo Serafini & Armando Stellato (University of Rome Tor Vergata), basili@info.uniroma2.it, medium likelihood
  • Man-Kwan Shan & Fang-Fei Kuo (National Cheng Chi University), mkshan@cs.nccu.edu.tw, medium likelihood


Evaluation Procedures

Entries will be evaluated based on their success rates with respect ot both fine and coarse classifications. Entrants will have the option of enabling their software to output classifications of "unknown," which will be penalized less severely during evaluation than misclassifications, as classifications flagged as uncertain are much better than false classifications in a practical context. Evaluation will be performed using 5-fold cross validation.

Submissions in C/C++, Java, MatLab and Python (and other languages?) will be accepted.


Relevant Test Collections

  • On-line repositories of MIDI files (sample links available at www.music.mcgill.ca/~cmckay/midi.html)
  • Research databases.

Review 1

Review 2

This is an interesting topic, one that I haven't seen much work on. I do not believe that its difficult to get a large collection of midi files. Many are in public domain, were never intended to be copyrighted, or have copyleft / creative commons licences. However, its still difficult to assemble a reasonable collection of midi files of appropriate length which accurately represent a sufficient number of genres. This must be addressed.

A key point is that it requires the Contest Committee to handlabel a large number of midi files. We also need to determine what our genres are. Is the Committee capable and willing to do this? I personally would find it very difficult to determine the genre of a midi recording which I don't recognize. MIDI all sounds like Muzak to me, unless I know the original audio recording. Has anyone tried midi-based genre classification before?

I have no problems with the suggested evaluation and testing procedures.

I think we need some more feedback on whether people are really interested in this. Most researchers who use MIDI, to my knowledge, aren't concerned with genre issues. George typically works with audio, so the proposer is the only one I'm aware of who I know is interested. I could be wrong so lets ask around. We also need to explore the handlabelling task, and to see if we can assemble a decent collection (which we should do regardless of this proposal).

If there is significant interest, and the labeling can be done, then we should accept it.