2009:Query by Tapping

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Revision as of 22:45, 7 September 2009 by Jin-Da Chen (talk | contribs)

Overview

The text of this section is copied from the 2008 page. Please add your comments and discussions for 2009.

The main purpose of QBT (Query by Tapping) is to evaluate MIR system in retrieving ground-truth MIDI files by tapping the onset of music notes to the microphone. This task provides query files in wave format as well as the corresponding human-label onset time in symbolic format. For this year's QBT task, we have two corpora for evaluation:

  • Roger Jang's MIR-QBT: This dataset contains both wav files (recorded via microphone) and onset files (human-labeled onset time).
  • Show Hsiao's QBT_symbolic: This dataset contains only onset files (obtained from the user's tapping on keyboard).

Task description

Subtask 1: QBT with symbolic input

  • Test database: About 150 ground-truth monophonic MIDI files in MIR-QBT.
  • Query files: About 800 text files of onset time to retrieve target MIDIs in MIR_QBT. These onset files can help participant concentrate on similarity matching instead of onset detection. All onset files cannot guarantee to have perfect detection result from original wav query files.
  • Evaluation: Return top 10 candidates for each query file. 1 point is scored for a hit in the top 10 and 0 is scored otherwise (Top-10 hit rate).

Subtask 2: QBT with wave input

  • Test database: About 150 ground-truth monophonic MIDI files in MIR-QBT.
  • Query files: About 800 wave files of tapping recordings to retrieve MIDIs in MIR-QBT.
  • Evaluation: Return top 10 candidates for each query file. 1 point is scored for a hit in the top 10 and 0 is scored otherwise (Top-10 hit rate).

Disucussions for 2009

Jin-Da's Comments 12/08/2009

We are going to have three datasets for QBT this year. Two sets are wav files (obtained from tapping on the microphone) with human labelled onset information. The other set is purely onset data obtained from computer keyboard input. Download URL of these datasets will be posted here soon.

Jin-Da's Comments 12/08/2009

I think we should have two subtasks for QBT.

  1. Subtask 1: Use the human-labeled onset time for comparison directly.
  2. Subtask 2: Use wav files for onset detection and then perform comparison.

Command formats

Indexing the MIDIs collection

Command format should look like this:

indexing %dbMidi.list% %dir_workspace_root%

where %dbMidi.list% is the input list of database midi files named as uniq_key.mid. For example:

QBT/database/00001.mid
QBT/database/00002.mid
QBT/database/00003.mid
QBT/database/00004.mid
...

Output indexed files are placed into %dir_workspace_root%. (Note that this step is not required unless you want to index or preprocess the midi database.)

Test the query files

The command format should be like this:

qbtProgram %dbMidi_list% %query_file_list% %resultFile% %dir_workspace_root%

You can use %dir_workspace_root% to store any temporary indexing/database structures. (You can omit %dir_workspace_root% if you do not need it at all.) If the input query files are onset files (for subtask 1), then the format of %query_file_list% is like this:

qbtQuery/query_00001.onset
qbtQuery/query_00002.onset
qbtQuery/query_00003.onset
...

(Pleae refer to the readme.txt of the downloaded MIR-QBT corpus for the format of onset files.)

If the input query files are wave files (for subtask 2), the the format of %query_file_list% is like this:

qbtQuery/query_00001.wav
qbtQuery/query_00002.wav
qbtQuery/query_00003.wav
...

The result file gives top-10 candidates for each query. For instance, for wave query file, the result file should have the following format for subtask 1:

qbtQuery/query_00001.onset: 00025 01003 02200 ... 
qbtQuery/query_00002.onset: 01547 02313 07653 ... 
qbtQuery/query_00003.onset: 03142 00320 00973 ... 
...

And for subtask 2:

qbtQuery/query_00001.wav: 00025 01003 02200 ... 
qbtQuery/query_00002.wav: 01547 02313 07653 ... 
qbtQuery/query_00003.wav: 03142 00320 00973 ... 
...

Submission closing date

Sept. 15, 2009

Interested Participants

  • Pierre Hanna, Matthias Robine, SIMBALS, University of Bordeaux, France. hanna at labri dot fr
  • Jin-Da Chen, Jyh-Shing Roger Jang, Department of Computer Science, National Tsing-Hua University, Hsinchu, Taiwan. cdc at mirlab dot org
  • Shu-Jen Show Hsiao, Tyne Liang, Department of Computer Science, National Chiao-Tung University, Hsinchu, Taiwan, R.O.C, show.cs95g at nctu.edu.tw