Abstract
Musical patterns that recur in approximate, rather than identical, form within the body of a musical work are considered to be of considerable importance in music analysis. Here we consider the “evolutionary chain problem”: this is the problem of computing a chain of all “motif” recurrences, each of which is a transformation of (“similar” to) the original motif, but each of which may be progressively further from the original. Here we consider several variants of the evolutionary chain problem and we present efficient algorithms and implementations for solving them.
Partially supported by the Royal Society grant CCSLAAR.
Partially supported by an ORS studentship.
This is a preview of subscription content, log in via an institution.
Buying options
Tax calculation will be finalised at checkout
Purchases are for personal use only
Learn about institutional subscriptionsPreview
Unable to display preview. Download preview PDF.
References
A. Apostolico and F. P. Preparata, Optimal Off-line Detection of Repetitions in a String, Theoretical Computer Science, 22 3, pp. 297–315 (1983). 309
E. Cambouropoulos, A General Pitch Interval Representation: Theory and Applications, Journal of New Music Research 25, pp. 231–251 (1996). 307
E. Cambouropoulos, T. Crawford and C. S. Iliopoulos, (1999) Pattern Processing in Melodic Sequences: Challenges, Caveats and Prospects. In Proceedings of the AISB’99 Convention (Artificial Intelligence and Simulation of Behaviour), Edinburgh, U.K., pp. 42–47 (1999). 307
T. Crawford, C. S. Iliopoulos and R. Raman, String Matching Techniques for Musical Similarity and Melodic Recognition, Computing in Musicology, Vol 11, pp. 73–100 (1998). 307
T. Crawford, C. S. Iliopoulos, R. Winder and H. Yu, Approximate musical evolution, in the Proceedings of the 1999 Artificial Intelligence and Simulation of Behaviour Symposium (AISB’99), G. Wiggins (ed), The Society for the Study of Artificial Intelligence and Simulation of Behaviour, Edinburgh, pp. 76–81 (1999). 317
M. Crochemore, An optimal algorithm for computing the repetitions in a word, Information Processing Letters 12, pp. 244–250 (1981). 309
M. Crochemore, C. S. Iliopoulos and H. Yu, Algorithms for computing evolutionary chains in molecular and musical sequences, Proceedings of the 9-th Australasian Workshop on Combinatorial Algorithms Vol 6, pp. 172–185 (1998). 317
C. S. Iliopoulos and L. Mouchard, An O(n log n) algorithm for computing all maximal quasiperiodicities in strings, Proceedings of CATS’99: ”Computing: Australasian Theory Symposium“, Auckland, New Zealand, Lecture Notes in Computer Science, Springer Verlag, Vol 21 3, pp. 262–272 (1999). 309
C. S. Iliopoulos, D. W. G. Moore and K. Park, Covering a string, Algorithmica 16, pp. 288–297 (1996). 309
C. S. Iliopoulos and Y. J. Pinzon, The Max-Shift Algorithm, submitted. 312
G.M. Landau and U. Vishkin, Fast parallel and serial approximate string matching, in Journal of Algorithms 10, pp. 157–169 (1989). 309
G. M. Landau and J. P. Schmidt, An algorithm for approximate tandem repeats, in Proc. Fourth Symposium on Combinatorial Pattern Matching, Springer-Verlag Lecture Notes in Computer Science 648, pp. 120–133 (1993). 309
G. M. Landau and U. Vishkin, Introducing efficient parallelism into approximate string matching and a new serial algorithm, in Proc. Annual ACM Symposium on Theory of Computing, ACM Press, pp. 220–230 (1986). 311, 312
G. Main and R. Lorentz, An O(n log n) algorithm for finding all repetitions in a string, Journal of Algorithms 5, pp. 422–432 (1984). 309
E. W. Myers, A Fast Bit-Vector Algorithm for Approximate String Matching Based on Dynamic Progamming, in Journal of the ACM 46 3, pp. 395–415 (1999). 311
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2000 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Crochemore, M., Iliopoulos, C.S., Pinzon, Y.J. (2000). Fast Evolutionary Chains. In: Hlaváč, V., Jeffery, K.G., Wiedermann, J. (eds) SOFSEM 2000: Theory and Practice of Informatics. SOFSEM 2000. Lecture Notes in Computer Science, vol 1963. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44411-4_19
Download citation
DOI: https://doi.org/10.1007/3-540-44411-4_19
Published:
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-41348-6
Online ISBN: 978-3-540-44411-4
eBook Packages: Springer Book Archive