Musical Note and Instrument Classification With Likelihood-Frequency Analysis and Support Vector Machines
| dc.contributor.author | Özbek, Mehmet Erdal | |
| dc.contributor.author | Delpha, Claude | |
| dc.contributor.author | Duhamel, Pierre | |
| dc.date.accessioned | 2016-08-08T08:29:40Z | |
| dc.date.available | 2016-08-08T08:29:40Z | |
| dc.date.issued | 2007 | |
| dc.description | 15th European Signal Processing Conference, EUSIPCO 2007; Poznan; Poland; 3 September 2007 through 7 September 2007 | en_US |
| dc.description.abstract | In this paper, we analyze the classification performance of a likelihood-frequency-time (LiFT) analysis designed for partial tracking and automatic transcription of music using support vector machines. The LiFT analysis is based on constant-Q filtering of signals with a filter-bank designed to filter 24 quarter-tone frequencies of an octave. Using the LiFT information, features are extracted from the isolated note samples and classification of instruments and notes is performed with linear, polynomial and radial basis function kernels. Correct classification ratios are obtained for 19 instrument and 36 notes. | en_US |
| dc.identifier.citation | Özbek, M. E., Delpha, C., and Duhamel, P. (2007). Musical note and instrument classification with likelihood-frequency-time analysis and support vector machines. Paper presented at the 15th European Signal Processing Conference, EUSIPCO 2007, Poznan, Poland, 3-7 September (pp.941-945). Piscataway, N.J.: IEEE | en_US |
| dc.identifier.issn | 2219-5491 | |
| dc.identifier.scopus | 2-s2.0-79953712402 | |
| dc.identifier.uri | https://hdl.handle.net/11147/2062 | |
| dc.language.iso | en | en_US |
| dc.publisher | Institute of Electrical and Electronics Engineers Inc. | en_US |
| dc.relation.ispartof | 15th European Signal Processing Conference, EUSIPCO 2007 | en_US |
| dc.rights | info:eu-repo/semantics/openAccess | en_US |
| dc.subject | Instruments | en_US |
| dc.subject | Automatic transcription | en_US |
| dc.subject | Classification performance | en_US |
| dc.subject | Correct classification ratios | en_US |
| dc.subject | Lift analysis | en_US |
| dc.subject | Signal processing | en_US |
| dc.title | Musical Note and Instrument Classification With Likelihood-Frequency Analysis and Support Vector Machines | en_US |
| dc.type | Conference Object | en_US |
| dspace.entity.type | Publication | |
| gdc.author.institutional | Özbek, Mehmet Erdal | |
| gdc.author.yokid | 107862 | |
| gdc.coar.access | open access | |
| gdc.coar.type | text::conference output | |
| gdc.description.department | İzmir Institute of Technology. Electrical and Electronics Engineering | en_US |
| gdc.description.endpage | 945 | en_US |
| gdc.description.publicationcategory | Konferans Öğesi - Uluslararası - Kurum Öğretim Elemanı | en_US |
| gdc.description.scopusquality | Q3 | |
| gdc.description.startpage | 941 | en_US |
| gdc.description.wosquality | N/A | |
| gdc.index.type | Scopus | |
| gdc.scopus.citedcount | 5 | |
| relation.isOrgUnitOfPublication.latestForDiscovery | 9af2b05f-28ac-4003-8abe-a4dfe192da5e |