Arbeitspapier
Prediction of notes from vocal time series produced by singing voice
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.
- Sprache
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Englisch
- Erschienen in
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Series: Technical Report ; No. 2003,01
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Garczarek, Ursula
Weihs, Claus
Ligges, Uwe
- Ereignis
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Veröffentlichung
- (wer)
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Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
- (wo)
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Dortmund
- (wann)
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2003
- Handle
- Letzte Aktualisierung
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10.03.2025, 11:43 MEZ
Datenpartner
Dieses Objekt wird bereitgestellt von:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Garczarek, Ursula
- Weihs, Claus
- Ligges, Uwe
- Universität Dortmund, Sonderforschungsbereich 475 - Komplexitätsreduktion in Multivariaten Datenstrukturen
Entstanden
- 2003
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