17 May 2012
Understanding the Virtuoso: Exploring Music and Performance with Software
Meeting Room 10, 2nd Floor, JLB
12:30pm - 13:45pm
Dr Nicolas Gold - University College London
There are many applications of computing in support of music analysis. In this talk I will discuss two recent pieces of research in this area. The first aimed to investigate why we prefer listening to some musicians rather than others playing the same pieces (a search for "performance
motive"). I will discuss the methodology we developed that uses automated clustering techniques to analyse a larger corpus of recorded performances than would be easily tractable for an analyst working alone. The method characterises the performed shape of structural aspects of the music and allows comparison between performers. The second piece of research addresses the problem of clone detection in patches written in the Max/MSP programming language, widely used for interactive music and art. The problems of clone detection are somewhat different for graphical data-flow languages like Max/MSP in comparison to traditional languages, and require a new
approach to source code analysis.
Nicolas Gold is a Senior Lecturer in the Department of Computer Science at University College London (UCL) and received his Ph.D. from the University of Durham, UK, in 2000. He undertakes research in music computing, software engineering and the digital humanities and has published widely in these areas. He is a member of the Centre for Research in Evolution, Search, and Testing (CREST), an affiliate member of the UCL Centre for Digital Humanities, and an Associate of the AHRC Research Centre for Musical Performance as Creative Practice (CMPCP).
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