أعرض تسجيلة المادة بشكل مبسط

dc.creator Grachten, Maarten
dc.creator Arcos, Josep Ll.
dc.creator Lopez de Mantaras, Ramon
dc.date 2008-03-18T15:09:15Z
dc.date 2008-03-18T15:09:15Z
dc.date 2006
dc.date.accessioned 2017-01-31T01:00:44Z
dc.date.available 2017-01-31T01:00:44Z
dc.identifier Proceedings of the Twenty-First National Conference on Artificial Intelligence, AAAI-06: July 16–20, 2006, Boston, Massachusetts. AAAI Press, Vol. 2, p.p.: 1609-1612.
dc.identifier 978-1-57735-281-5
dc.identifier http://hdl.handle.net/10261/3250
dc.identifier.uri http://dspace.mediu.edu.my:8181/xmlui/handle/10261/3250
dc.description The original publication is available at www.aaai.org
dc.description The research described in this paper focuses on global tempo transformations of monophonic audio recordings of saxophone jazz performances. More concretely, we have investigated the problem of how a performance played at a particular tempo can be automatically rendered at another tempo while preserving its expressivity. To do so we have developed a case-based reasoning system called TempoExpress. The results we have obtained have been extensively compared against a standard technique called uniform time stretching (UTS), and show that our approach is superior to UTS.
dc.description Peer reviewed
dc.format 262668 bytes
dc.format application/pdf
dc.language eng
dc.rights openAccess
dc.subject Artificial Intelligence
dc.subject Case-Based Reasoning
dc.subject CBR
dc.subject Computational Models of Music
dc.title TempoExpress: An Expressivity-Preserving Musical Tempo Transformation
dc.type Comunicación de congreso


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أعرض تسجيلة المادة بشكل مبسط