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14
Towards a general computational theory of musical structure
, 1998
"... The General Computational Theory of Musical Structure (GCTMS) is a theory that may be employed to obtain a structural description (or set of descriptions) of a musical surface. This theory is based on general cognitive and logical principles, is independent of any specific musical style or idiom, ..."
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Cited by 68 (3 self)
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The General Computational Theory of Musical Structure (GCTMS) is a theory that may be employed to obtain a structural description (or set of descriptions) of a musical surface. This theory is based on general cognitive and logical principles, is independent of any specific musical style or idiom, and can be applied to any musical surface. The musical work is presented to GCTMS as a sequence of discrete symbolically represented events (e.g. notes) without higherlevel structural elements (e.g. articulation marks, timesignature etc.) although such information may be used to guide the analytic process. The aim of the application of the theory is to reach a structural description of the musical work that may be considered as 'plausible' or 'permissible' by a human music analyst. As styledependent knowledge is not embodied in the general theory, highly sophisticated analyses (similar to those an expert analyst may provide) are not expected. The theory gives, however, higher rating to descriptions that may be considered more reasonable or acceptable by human analysts and lower to descriptions that are less plausible.
Pattern Processing in Melodic Sequences: Challenges, Caveats and Prospects
 In Proceedings of the AISB'99 Convention (Arti Intelligence and Simulation of Behaviour
, 1999
"... In this paper a number of issues relating to the application of string processing techniques on musical sequences are discussed. A brief survey of some musical string processing algorithms is given and some issues of melodic representation, abstraction, segmentation and categorisation are presented. ..."
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Cited by 37 (13 self)
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In this paper a number of issues relating to the application of string processing techniques on musical sequences are discussed. A brief survey of some musical string processing algorithms is given and some issues of melodic representation, abstraction, segmentation and categorisation are presented. This paper is not intended towards providing solutions to string processing problems but rather towards highlighting possible stumblingblock areas and raising awareness of primarily musicrelated particularities that can cause problems in matching applications. 1.
Approximate string matching in musical sequences
 In Proceedings of the Prague Stringology Conference
, 2001
"... Abstract. Here we consider computational problems on ffiapproximate and(ffi; fl)approximate string matching. These are two new notions of approximate matching that arise naturally in applications of computer assisted music analysis. We present fast, efficient and practical algorithms for these tw ..."
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Abstract. Here we consider computational problems on ffiapproximate and(ffi; fl)approximate string matching. These are two new notions of approximate matching that arise naturally in applications of computer assisted music analysis. We present fast, efficient and practical algorithms for these two notions of approximate string matching.
A Bitparallel Suffix Automaton Approach for (δ, γ)Matching in Music Retrieval
"... (delta,gamma)Matching is a string matching problem with applications to music retrieval. The goal is, given a pattern P1...m and a text T1...n on an alphabet of integers, find the occurrences P of the pattern in the text such that (i) 81 i m; jP i P i j . Several techniques for (delta,gamma)mat ..."
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Cited by 11 (2 self)
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(delta,gamma)Matching is a string matching problem with applications to music retrieval. The goal is, given a pattern P1...m and a text T1...n on an alphabet of integers, find the occurrences P of the pattern in the text such that (i) 81 i m; jP i P i j . Several techniques for (delta,gamma)matching have been proposed. In this paper we show that a classical string matching technique that combines bitparallelism and sux automata can be successfully adapted to this problem. This is the first characterskipping algorithm that skips characters using both delta and gamma. We implemented our algorithm and drew experimental results on real music showing that our algorithm is superior to current alternatives.
Approximate String Matching with Gaps
, 2002
"... In this paper we consider several new versions of approximate string matching with gaps. The main characteristic of these new versions is the existence of gaps in the matching of a given pattern in a text. Algorithms are sketched for each version and their time and space complexity is stated. The sp ..."
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Cited by 11 (1 self)
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In this paper we consider several new versions of approximate string matching with gaps. The main characteristic of these new versions is the existence of gaps in the matching of a given pattern in a text. Algorithms are sketched for each version and their time and space complexity is stated. The specific versions of approximate string matching have various applications in computerized music analysis.
Computing Approximate Repetitions in Musical Sequences
 In Proceedings of Prague Stringology Club Workshop PSCW’00
, 2000
"... . Here we present new algorithms for computing all approximate and ( ..."
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Cited by 5 (0 self)
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. Here we present new algorithms for computing all approximate and (
Extracting significant patterns from musical strings
 In Proceedings of the AISB’99 Convention (Artificial Intelligence and Simulation of Behaviour
, 2000
"... In this paper a number of issues relating to the application of string processing techniques on musical sequences are discussed. Special attention is given to musical pattern extraction. Firstly, a number of general problems are presented in terms of musical representation and pattern processing met ..."
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Cited by 3 (0 self)
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In this paper a number of issues relating to the application of string processing techniques on musical sequences are discussed. Special attention is given to musical pattern extraction. Firstly, a number of general problems are presented in terms of musical representation and pattern processing methodologies. Then a number of interesting melodic pattern matching problems are presented. Finally, issues relating to pattern extraction are discussed, with special attention being drawn to defining musical pattern ‘significance’. This paper is not intended towards providing solutions to string processing problems but rather towards raising awareness of primarily musicrelated particularities that can cause problems in matching applications and also suggesting some interesting string processing problems that require efficient computational solutions. 1.
Three Heuristics for δMatching: δBM Algorithms
, 2002
"... We consider a version of pattern matching useful in processing large musical data: deltamatching, which consists in finding matches which are deltaapproximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance betw ..."
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We consider a version of pattern matching useful in processing large musical data: deltamatching, which consists in finding matches which are deltaapproximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance between two symbols a, b is measured as a  b. We present deltamatching algorithms fast on the average providing that the pattern is "nonflat"and the alphabet interval is large. The pattern is "flat" if its structure does not vary substantially. We also consider (delta, gamma)matching, where gamma is a bound on the total number of errors. The algorithms, named deltaBM1, deltaBM2 and deltaBM3 can be thought as members of the generalized BoyerMoore family of algorithms. The algorithms are fast on average. This is the first paper on the subject, previously only "occurrence heuristics" have been considered. Our heuristics are much stronger and refer to larger parts of texts (not only to single positions). We use deltaversions of...
Bitparallel (δ,γ)Matching and Suffix Automata
"... Matching is a string matching problem with applications to music retrieval. The goal is, given a pattern P 1...m and a text T 1...n on an alphabet of integers, find the occurrences P # of the pattern in the text such that (i) P # i #, and (ii) #. The problem makes sense for # ..."
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Matching is a string matching problem with applications to music retrieval. The goal is, given a pattern P 1...m and a text T 1...n on an alphabet of integers, find the occurrences P # of the pattern in the text such that (i) P # i #, and (ii) #. The problem makes sense for # #m. Several techniques for (#, #)matching have been proposed, based on bitparallelism or on skipping characters. We first present an O(n log(#)/w) worstcase time and O(n) averagecase time bitparallel algorithm (being w the number of bits in the computer word). It improves the previous O(n log(#m)/w) worstcase time algorithm of the same type. Second, we combine our bitparallel algorithm with su#x automata to obtain the first algorithm that skips characters using both # and #. This algorithm examines less characters than any previous approach, as the others do just #matching and check the #condition on the candidates. We implemented our algorithms and drew experimental results on real music, showing that our algorithms are superior to current alternatives with high values of #.
Occurrence and Substring Heuristics for \delta Matching
, 2013
"... We consider a version of pattern matching useful in processing large musical data:matching, which consists in finding matches which areapproximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance between two sy ..."
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We consider a version of pattern matching useful in processing large musical data:matching, which consists in finding matches which areapproximate in the sense of the distance measured as maximum difference between symbols. The alphabet is an interval of integers, and the distance between two symbols, is measured as. We also considermatching, where is a bound on the total sum of the differences. We first consider “occurrence heuristics ” by adapting exact string matching algorithms to the two notions of approximate string matching. The resulting algorithms are efficient in practice. Then we consider “substring heuristics”. We presentmatching algorithms fast on the average providing that the pattern is “nonflat” and the alphabet interval is large. The pattern is “flat” if its structure does not vary substantially. The algorithms, namedBM1,BM2 andBM3 can be thought as members of the generalized BoyerMoore family of algorithms. The algorithms are fast on average. This is the first paper on the subject, previously only “occurrence heuristics” have been considered. Our substring heuristics are much stronger and refer