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Musical instrument identification using principal componant analysis and multi-layered perceptions

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Show simple item record Loughran, Róisín Walker, Jacqueline O'Neill, Michael O'Farrell, Marion 2009-03-13T14:04:50Z 2009-03-13T14:04:50Z 2008
dc.description peer-reviewed
dc.description.abstract This study aims to create an automatic musical instrument classifier by extracting audio features from real sample sounds. These features are reduced using Principal Component Analysis and the resultant data is used to train a Multi-Layered Perceptron. We found that the RMS temporal envelope and the evolution of the centroid gave the most interesting results of the features studied. These results were found to be competitive whether the scope of the data was across one octave or across the range of each instrument
dc.language.iso eng en
dc.publisher IEEE Computer Society en
dc.relation.ispartofseries 2008 International Conference on Audio, Language and Image Processing pp. 643-648
dc.rights © 2008 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.”
dc.subject musical instrument en
dc.title Musical instrument identification using principal componant analysis and multi-layered perceptions en
dc.type Conference item en
dc.type.supercollection all_ul_research en
dc.type.restriction none en
dc.type.restriction none en
dc.identifier.doi 10.1109/ICALIP.2008.4590236
dc.identifier.local 09ece03
dc.contributor.sponsor SFI
dc.internal.rssid 1130557

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