Timbre recognition of single notes using an ARTMAP neural network

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dc.contributor.author Fragoulis, D en
dc.contributor.author Avaritsiotis, J en
dc.contributor.author Papaodysseus, C en
dc.date.accessioned 2014-03-01T01:48:26Z
dc.date.available 2014-03-01T01:48:26Z
dc.date.issued 1999 en
dc.identifier.uri http://hdl.handle.net/123456789/25478
dc.subject Musical Instruments en
dc.subject Neural Network en
dc.subject Neural Network Model en
dc.title Timbre recognition of single notes using an ARTMAP neural network en
heal.type journalArticle en
heal.identifier.primary 10.1109/ICECS.1999.813404 en
heal.identifier.secondary http://dx.doi.org/10.1109/ICECS.1999.813404 en
heal.publicationDate 1999 en
heal.abstract In this paper, a model for the perception of musical instrument timbre is presented. The model uses an ARTMAP neural network to distinguish single notes played by five different instruments. The duration of each note is quite short. The recognition of timbre is based on three acoustic properties: spectral synchrony, slope of the attacks and spectral distribution. Arrays of values en
dc.identifier.doi 10.1109/ICECS.1999.813404 en

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