Style Recognition in Music with Context Free Grammars and Kolmogorov Complexity
Abstract
The Kolmogorov Complexity of an object is incomputable. But built in its structure
is a way to specify description methods of an object that is computable in some sense.
Such a description method then can be exploited to quantify the bits of information needed
to generate the object from scratch. We show that Context-Free Grammars form such a viable description method to specify an object and the size of the grammar can be used to estimate the Kolmogorov Complexity. We use such estimation in approximating the Information
Distance between two musical strings. We also show that such distance measure in music
can be used to recognize the genre, composer and style and also for music classification.
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Cite this version of the work
Tiasa Mondol
(2020).
Style Recognition in Music with Context Free Grammars and Kolmogorov Complexity. UWSpace.
http://hdl.handle.net/10012/15689
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