Expressivity-preserving tempo transformation for music: a case-based approach

Authors:
Ramon López De Mántaras;Maarten Grachten;Josep-Lluís Arcos
Affiliations:
IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain;IIIA, Artificial Intelligence Research Institute, CSIC, Spanish Council for Scientific Research, Bellaterra, Catalonia, Spain
Venue:
KI'06 Proceedings of the 29th annual German conference on Artificial intelligence
Year:
2006

Citing 2
Cited 0

Constructive Adaptation

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The Cognition of Basic Musical Structures

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Abstract

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 develppoped 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.