Full metadata record
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Garczarek, Ursula | de |
dc.contributor.author | Ligges, Uwe | de |
dc.contributor.author | Weihs, Claus | de |
dc.date.accessioned | 2004-12-06T18:39:42Z | - |
dc.date.available | 2004-12-06T18:39:42Z | - |
dc.date.issued | 2003 | de |
dc.identifier.uri | http://hdl.handle.net/2003/4921 | - |
dc.identifier.uri | http://dx.doi.org/10.17877/DE290R-6842 | - |
dc.description.abstract | Aiming at optimal prediction of the correct note corresponding to a vocal time series we trained a classification algorithm on the basis of parts of interpretations of Tochter Zion (Händel) and tested the algorithm on the remaining parts. As classification algorithm we use a radial basis function support vector machine together with a “Hidden Markov” method as a dynamisation mechanism and some smoothing for categorical data. With this we were able to obtain a minimum of 5% average classification error and a maximum of 26% on data from an experiment with 16 singers. | en |
dc.format.extent | 309399 bytes | - |
dc.format.mimetype | application/pdf | - |
dc.language.iso | en | de |
dc.publisher | Universitätsbibliothek Dortmund | de |
dc.subject | radial basis functions | en |
dc.subject | support vector machines | en |
dc.subject | classification | en |
dc.subject | time series | en |
dc.subject | prediction | en |
dc.subject | singing voice | en |
dc.subject.ddc | 310 | de |
dc.title | Prediction of Notes from Vocal Time Series Produced by Singing Voice | en |
dc.type | Text | de |
dc.type.publicationtype | report | en |
dcterms.accessRights | open access | - |
Appears in Collections: | Sonderforschungsbereich (SFB) 475 |
Files in This Item:
File | Description | Size | Format | |
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tr01-03.pdf | DNB | 302.15 kB | Adobe PDF | View/Open |
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