Presentation	2007-11-19 The clustering of MIDI music using Self-Organizing Map Kouhei Tanaka, Hiroshi Dozono,
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Abstract(in English)	As the classification system of musical information, we propose a clustering method of MIDI music data using Self Organizing Maps(SOM). MIDI data are made from scores of music consist all information for playing the music. In this research, the MIDI data are translated to the input vectors to SOM for each phrase and for each song. We examine the ability of the classification according to the genre of music (Rock, Jazz, Blues, Country, Latin. etc.) as the results of learning using SOM.
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Keyword(in English)	Self-Organizing Map / Musical information processing / MIDI
Paper #	NC2007-69
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Committee	NC
Conference Date	2007/11/11(1days)
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Registration To	Neurocomputing (NC)
Language	JPN
Title (in Japanese)	(See Japanese page)
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Title (in English)	The clustering of MIDI music using Self-Organizing Map
Sub Title (in English)
Keyword(1)	Self-Organizing Map
Keyword(2)	Musical information processing
Keyword(3)	MIDI
1st Author's Name	Kouhei Tanaka
1st Author's Affiliation	The Department of Advanced Systems Control Engineering Graduate School of Science and Engineering, Saga University()
2nd Author's Name	Hiroshi Dozono
2nd Author's Affiliation	The Department of Advanced Systems Control Engineering Graduate School of Science and Engineering, Saga University
Date	2007-11-19
Paper #	NC2007-69
Volume (vol)	vol.107
Number (no)	328
Page	pp.pp.-
#Pages	6
Date of Issue