Presentation 2003/6/20
Chord Recognition Using Gaussian Mixture Model
Masato SUGANO, Keiichiro SHIRAI, Takayuki NAGAI, Masaaki IKEHARA,
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Abstract(in English) In this paper, the method of recognizing the chord of a musical piece using a gaussian mixture model (GMM) is proposed, and an experiment examination result is reported. The input sound signal from frame division is divided for every octave using filterbank, and the power spectrum corresponding to 12 sound name is extracted as a 12-dimensional vector from each octave. It asks for mixed dignity, an average vector, and a covariance matrix from this vector, and GMM is formed from these. Additionally, by using N-gram model together, the model is in consideration of chord progression. And above, it can be adapted to non-learned range, and the method of the case of a complicated composition sound on real time into consideration in the future is proposed.
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Keyword(in English) gaussian mixture model / N-gram model / chord recognition / pitch extraction / music understanding
Paper # DSP2003-56
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Conference Information
Committee DSP
Conference Date 2003/6/20(1days)
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Registration To Digital Signal Processing (DSP)
Language JPN
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Chord Recognition Using Gaussian Mixture Model
Sub Title (in English)
Keyword(1) gaussian mixture model
Keyword(2) N-gram model
Keyword(3) chord recognition
Keyword(4) pitch extraction
Keyword(5) music understanding
1st Author's Name Masato SUGANO
1st Author's Affiliation Keio University()
2nd Author's Name Keiichiro SHIRAI
2nd Author's Affiliation Keio University
3rd Author's Name Takayuki NAGAI
3rd Author's Affiliation The University of Electro-Communications
4th Author's Name Masaaki IKEHARA
4th Author's Affiliation Keio University
Date 2003/6/20
Paper # DSP2003-56
Volume (vol) vol.103
Number (no) 147
Page pp.pp.-
#Pages 6
Date of Issue