Automatic Music Transcription from Multiphonic MIDI Signals

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dc.contributor.author Haruto Takeda en_US
dc.contributor.author Takuya Nishimoto en_US
dc.contributor.author Shigeki Sagayama en_US
dc.contributor.editor Holger H. Hoos en_US
dc.contributor.editor David Bainbridge en_US
dc.date.accessioned 2004-10-21T04:26:41Z
dc.date.available 2004-10-21T04:26:41Z
dc.date.issued 2003-10-26 en_US
dc.identifier.isbn 0-9746194-0-X en_US
dc.identifier.uri http://jhir.library.jhu.edu/handle/1774.2/53
dc.description.abstract For automatically transcribing human-performed polyphonic music recorded in the MIDI format, rhythm and tempo are decomposed through probabilistic modeling using Viterbi search in HMM for recognizing the rhythm and EM algorithm for estimating the tempo. Experimental evaluation are also presented. en_US
dc.description.provenance Made available in DSpace on 2004-10-21T04:26:41Z (GMT). No. of bitstreams: 1 paper.pdf: 86884 bytes, checksum: 8bf606ef665e48dc1785c81c179efc7d (MD5) Previous issue date: 2003-10-26 en
dc.format.extent 86884 bytes
dc.format.mimetype application/pdf
dc.language en en_US
dc.language.iso en_US
dc.publisher Johns Hopkins University en_US
dc.subject Music Analysis en_US
dc.subject Perception and Cognition en_US
dc.title Automatic Music Transcription from Multiphonic MIDI Signals en_US
dc.type article en_US

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