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29
Automatic Extraction of Tempo and Beat from Expressive Performances
 Journal of New Music Research
, 2001
"... We describe a computer program which is able to estimate the tempo and the times of musical beats in expressively performed music. The input data may be either digital audio or a symbolic representation of music such as MIDI. The data is processed offline to detect the salient rhythmic events and t ..."
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Cited by 193 (29 self)
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We describe a computer program which is able to estimate the tempo and the times of musical beats in expressively performed music. The input data may be either digital audio or a symbolic representation of music such as MIDI. The data is processed offline to detect the salient rhythmic events and the timing of these events is analysed to generate hypotheses of the tempo at various metrical levels. Based on these tempo hypotheses, a multiple hypothesis search nds the sequence of beat times which has the best fit to the rhythmic events. We show that estimating the perceptual salience of rhythmic events significantly improves the results. No prior knowledge of the tempo, meter or musical style is assumed; all required information is derived from the data. Results are presented for a range of different musical styles, including classical, jazz, and popular works with a variety of tempi and meters. The system calculates the tempo correctly in most cases, the most common error being a doubling or halving of the tempo. The calculation of beat times is also robust. When errors are made concerning the phase of the beat, the system recovers quickly to resume correct beat tracking, despite the fact that there is no high level musical knowledge encoded in the system.
Algorithms for Discovering Repeated Patterns in Multidimensional Representations of Polyphonic Music
, 2003
"... In this paper we give an overview of four algorithms that we have developed for pattern matching, pattern discovery and data compression in multidimensional datasets. We show that these algorithms can fruitfully be used for processing musical data. In particular, we show that our algorithms can disc ..."
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Cited by 65 (22 self)
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In this paper we give an overview of four algorithms that we have developed for pattern matching, pattern discovery and data compression in multidimensional datasets. We show that these algorithms can fruitfully be used for processing musical data. In particular, we show that our algorithms can discover instances of perceptually signifrant musica 1 repetition that cannot be found using previous approaches. We also describe results that suggest the possibility of using our datacompression algorithm for modelling expert motivicthematic music analysis.
From MIDI to Traditional Musical Notation
 In Proceedings of the AAAI Workshop on Artificial Intelligence
, 2000
"... In this paper a system that is designed to extract the musical score from a MIDI performance is described. The proposed system comprises of a number of modules that perform the following tasks: identification of elementary musical objects, calculation of accent (salience) of musical events, beat ind ..."
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Cited by 40 (6 self)
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In this paper a system that is designed to extract the musical score from a MIDI performance is described. The proposed system comprises of a number of modules that perform the following tasks: identification of elementary musical objects, calculation of accent (salience) of musical events, beat induction, beat tracking, onset quantisation, streaming, duration quantisation and pitch spelling. The system has been applied on 13 complete Mozart sonata performances giving very encouraging results.
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.
Pitch Spelling Algorithms
, 2003
"... In this paper I introduce a new algorithm called ps13 that reliably computes the correct pitch names (e.g., C#4, B#5 etc.) of the notes in a passage of tonal music, when given only the onsettime and MIDI note number of each note in the passage. ps13 correctly predicts the pitch names of 99.81% of t ..."
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Cited by 36 (11 self)
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In this paper I introduce a new algorithm called ps13 that reliably computes the correct pitch names (e.g., C#4, B#5 etc.) of the notes in a passage of tonal music, when given only the onsettime and MIDI note number of each note in the passage. ps13 correctly predicts the pitch names of 99.81% of the notes in a test corpus containing 41544 notes and consisting of all the pieces in the first book of J. S. Bach's Das Wohltemperirte Klavier (BWV 846869). Three previous algorithms (those of Cambouropoulos (1996, 1998, 2002), LonguetHiggins (1987) and Temperley (2001)) were run on the same corpus of 41544 notes. On this corpus, Cambouropoulos's algorithm made 2599 mistakes, LonguetHiggins 's algorithm made 265 mistakes and Temperley's algorithm made 122 mistakes. As ps13 made only 81 mistakes on the same corpus, this suggests that ps13 may be more robust than previous algorithms that attempt to perform the same task.
Automatic pitch spelling: From numbers to sharps and flats
 In Proceedings of the VIII Brazilian symposium on Computer Music
, 2001
"... In this paper a computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm input is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge is required such ..."
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Cited by 25 (1 self)
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In this paper a computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm input is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge is required such as key signature, tonal centers, time signature, voice separation and so on. Output of the algorithm is a sequence of ‘correctly ’ spelled pitches. The algorithm was evaluated on 8 complete piano sonatas by Mozart and had a success rate that is greater than 96% (10476 pitches were spelled correctly out of 10900 notes that required accidentals – overall number of pitches in 8 sonatas is 40058). The proposed algorithm was also compared to and tested against other pitch spelling algorithms. Pitch spelling algorithms are important not only for applications such as musical notation software packages but also for a multitude of tonal analytical tasks such as keyfinding and harmonic analysis. 1
Practical Algorithms for TranspositionInvariant StringMatching
"... We consider the problems of (1) longest common subsequence (LCS) of two given strings in the case where the first may be shifted by some constant (that is, transposed) to match the second, and (2) transpositioninvariant text searching using indel distance. These problems have applications in music ..."
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Cited by 10 (4 self)
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We consider the problems of (1) longest common subsequence (LCS) of two given strings in the case where the first may be shifted by some constant (that is, transposed) to match the second, and (2) transpositioninvariant text searching using indel distance. These problems have applications in music comparison and retrieval. We introduce two novel techniques to solve these problems efficiently. The first is based on the branch and bound method, the second on bitparallelism. Our branch and bound algorithm computes the longest common transpositioninvariant subsequence (LCTS) in time O((m&sup2;+log log sigma) log sigma) in the best case and O((m&sup2;+log sigma)sigma) in the worst case, where m and sigma, respectively, are the length of the strings and the size of the alphabet. On the other hand, we show that the same problem can be solved by using bitparallelism and thus obtain a speedup of O(w/ log m) over the classical algorithms, where the computer word has w bits. The advantage of this latter algorithm over the present bitparallel ones is that it allows the use of more complex distances, including general integer weights. Since our branch and bound method is very flexible, it can be further improved by combining it with other efficient algorithms such as our novel bitparallel algorithm. We experiment on several combination possibilities and discuss which are the best settings for each of those combinations. Our algorithms are easily extended to other musically relevant cases, such as deltamatching and polyphony (where there are several parallel texts to be considered). We also show how our bitparallel algorithm is adapted to text searching and illustrate its effectiveness in complex cases where the only known competing method is the use of brute force.
Pitch spelling: A computational model
 Music Perception
, 2003
"... In this article, cognitive and musicological aspects of pitch and pitch interval representations are explored via computational modeling. The specific task under investigation is pitch spelling, that is, how traditional score notation can be derived from a simple unstructured 12tone representation ..."
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Cited by 10 (0 self)
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In this article, cognitive and musicological aspects of pitch and pitch interval representations are explored via computational modeling. The specific task under investigation is pitch spelling, that is, how traditional score notation can be derived from a simple unstructured 12tone representation (e.g., pitchclass set or MIDI pitch representation). This study provides useful insights both into the domain of pitch perception and into musicological aspects of score notation strategies. A computational model is described that transcribes polyphonic MIDI pitch files into the Western traditional music notation. Input to the proposed algorithm is merely a sequence of MIDI pitch numbers in the order they appear in a MIDI file. No a priori knowledge such as key signature, tonal centers, time signature, chords, or voice separation is required. Output of the algorithm is a sequence of “correctly ” spelled pitches. The algorithm is based on an interval optimization approach that takes into account the frequency of occurrence of pitch intervals within the majorminor tonal scale framework. The algorithm was evaluated on 10 complete piano sonatas by Mozart and had a success rate of 98.8 % (634 pitches were spelled incorrectly out of a total of 54,418 notes); it was tested additionally on three Chopin waltzes and had a slightly worse success rate. The proposed pitch interval optimization approach is also compared with and tested against other pitchspelling strategies.
Flexible and efficient bitparallel techniques for transposition invariant approximate matching in music retrieval
 IN PROC. 10TH INT'L SYMP. ON STRING PROCESSING AND INFORMATION RETRIEVAL (SPIRE'03
, 2003
"... Recent research in music retrieval has shown that a combinatorial approach to the problem could be fruitful. Three distinguishing requirements of this particular problem are (a) approximate searching permitting missing, extra, and distorted notes, (b) transposition invariance, to allow matching a se ..."
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Cited by 8 (4 self)
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Recent research in music retrieval has shown that a combinatorial approach to the problem could be fruitful. Three distinguishing requirements of this particular problem are (a) approximate searching permitting missing, extra, and distorted notes, (b) transposition invariance, to allow matching a sequence that appears in a different scale, and (c) handling polyphonic music. These combined requirements make up a complex combinatorial problem that is currently under research. On the other hand, bitparallelism has proved a powerful practical tool for combinatorial pattern matching, both flexible and efficient. In this paper we use bitparallelism to search for several transpositions at the same time, and obtain speedups of O(w = log k) over the classical algorithms, where the computer word has w bits and k is the error threshold allowed in the match. Although not the best solution for the easier approximation measures, we show that our technique can be adapted to complex cases where no competing method exists, and that are the most interesting in terms of music retrieval.
Algorithms for computing evolutionary chains in molecular and musical sequences
 In: Proc. 9th Australasian Workshop on Combinatorial Algorithms
, 1998
"... Abstract. The problem of nding evolutionary chains is de ned as follows: given a string t (\the text") and a pattern p ( the \motif"), nd whether there exists a sequence u1 = p; u2; : : : ; ul occurring in the text t such that ui+1 occurs to the right of ui in t and ui and ui+1 are \simila ..."
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Cited by 7 (5 self)
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Abstract. The problem of nding evolutionary chains is de ned as follows: given a string t (\the text") and a pattern p ( the \motif"), nd whether there exists a sequence u1 = p; u2; : : : ; ul occurring in the text t such that ui+1 occurs to the right of ui in t and ui and ui+1 are \similar" (i.e. the di er by a certain number of symbols). Here we consider several variants of the evolutionary chain problem and we present e cient algorithms for solving them.