@inproceedings{Meredith_2016,
 abstract = {A computational approach to music analysis is presented, based on the compression of point-set representations of musical works. The approach relates closely to the theory of Kolmogorov complexity and to psychological coding theories of perceptual organisation. A sketch of a model of musical learning based on this approach is given and it is shown how the model accounts in principle for differences between individuals in how pieces of music are understood. The approach is implemented in a greedy compression algorithm, called COSIATEC, which partitions a point-set into the covered sets of translational equivalence classes of maximal translatable patterns. The analyses generated by COSIATEC on five fugues by J. S. Bach are presented and discussed. These analyses demonstrate the potential of the approach for automatically discovering musical patterns of thematic and structural importance.},
 author = {Meredith, David},
 title = {{Analysis by Compression: Automatic Generation of Compact Geometric Encodings of Musical Objects}},
 url_URN = {https://nbn-resolving.de/urn:nbn:de:bvb:12-babs2-0000007812},
 pages = {41--53},
 publisher = {{Bavarian State Library (BSB)}},
 editor = {Roland, Perry and Kepper, Johannes},
 booktitle = {{Music Encoding Conference Proceedings 2013 and 2014}},
 year = {2016},
 keywords = {mec-proceedings, mec-proceedings-2013},
 displayby = {Contributions from MEC 2013}
}

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