2009:Structural Segmentation

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Revision as of 11:07, 7 August 2009 by Matthiasmauch (talk | contribs) (Issues and Discussion)

The segment structure (or form) is one of the most important musical parameters. It is furthermore special because musical structure -- especially in popular music genres -- is accessible to everybody: it needs no particular musical knowledge.

Input: wave audio

Output: three column text file of the format <onset_time> <offset_time> <label>, i.e. like Chris Harte's chord labelling files (.lab). onset_time and offset_time in seconds, labels: 'A', 'B', ... where segments referring to the same structural element have the same label.

Ground truth data on audio is available for more than 200 songs, so given a quality measure everyone agrees on, evaluation wouldn't be harder than on other MIREX tasks. At the last ISMIR conference Lukashevich proposed a measure for segmentation evaluation.

Potential Participants

Matthias Mauch, Queen Mary, University of London --Matthias 08:49, 30 June 2009 (UTC)

Maarten Grachten, Johannes Kepler University, Linz, Austria -- Maarten

Geoffroy Peeters, IRCAM, Paris, France (depending on the kind of annotations)

Jouni Paulus, Tampere University of Technology, Finland

Stephan Huebler, Technical University of Dresden, Germany

Jordan Smith, McGill University, Montreal, Canada

Issues and Discussion

Thanks for the initiative! I might be interested in participating. Are you referring to segmentation of audio, or symbolic data? What set of annotated data did you refer to? [Maarten Grachten]

Yes, sorry, forgot to specify that. I'm mainly interested in audio, so I changed that above. --Matthias 11:04, 30 June 2009 (UTC)

The more the merrier: I could as well throw in the algo I implemented 2 years ago for my thesis [1]. I'm also curious about the annotated data mentioned. Thanks for your effort! --Ewald 17:33, 1 July 2009 (UTC)

Regarding ground truth: at Queen Mary we have the complete Beatles segmentations (with starts at bar beginnings), plus tens of other songs by Carole King, Queen, and Zweieck. We could leave the latter three untouched (i.e. I would not train my own algorithm on them), or publish them soon, so everyone can train their method on them. --Matthias 16:07, 7 August 2009 (UTC)