Results 1  10
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218
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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.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
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.
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.
unknown title
"... In this paper I introduce a new algorithm called ps13 that reliably computes the correct pitch names (e.g., C # 4, Bb5 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 % o ..."
Abstract
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.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
unknown title
"... Die Farbe ist die Taste, das Auge ist der Hammer.! Die Seele ist das Klavier mit vielen Saiten.! Der Künstler ist die Hand, die durch diese oder jene Taste! zweckmäßig die menschliche Seele in Vibration bringt. Wassily Kandinsky (1866 – 1944) ..."
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Die Farbe ist die Taste, das Auge ist der Hammer.! Die Seele ist das Klavier mit vielen Saiten.! Der Künstler ist die Hand, die durch diese oder jene Taste! zweckmäßig die menschliche Seele in Vibration bringt. Wassily Kandinsky (1866 – 1944)
Stylebook for the Tübingen Treebank of Written German (TüBaD/Z
, 2009
"... This stylebook is an updated version of Telljohann et al. (2009). It describes the design principles and the annotation scheme for the German treebank TüBaD/Z developed by the Division of Computational Linguistics (Lehrstuhl Prof. Hinrichs) at the Department of Linguistics (Seminar für Sprachwis ..."
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Cited by 55 (10 self)
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This stylebook is an updated version of Telljohann et al. (2009). It describes the design principles and the annotation scheme for the German treebank TüBaD/Z developed by the Division of Computational Linguistics (Lehrstuhl Prof. Hinrichs) at the Department of Linguistics (Seminar für Sprachwis
Question answering using constraint satisfaction
 Proceedings of the 42nd Meeting of the Association for Computational Linguistics (ACL'04
, 2004
"... QAbyDossierwithConstraints is a new approach to Question Answering whereby candidate answers ’ confidences are adjusted by asking auxiliary questions whose answers constrain the original answers. These constraints emerge naturally from the domain of interest, and enable application of realworld ..."
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Cited by 28 (2 self)
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QAbyDossierwithConstraints is a new approach to Question Answering whereby candidate answers ’ confidences are adjusted by asking auxiliary questions whose answers constrain the original answers. These constraints emerge naturally from the domain of interest, and enable application of realworld knowledge to QA. We show that our approach significantly improves system performance (75 % relative improvement in Fmeasure on select question types) and can create a “dossier ” of information about the subject matter in the original question.
Pattern Induction and matching in polyphonic music and other multidimensional datasets
 IN THE 5TH WORLD MULTICONFERENCE ON SYSTEMICS, CYBERNETICS AND INFORMATICS (SCI’2001), VOLUME X
, 2001
"... We present a new algorithm, SIA, which discovers maximal repeated patterns in any set of points in Cartesian spaces of any dimensionality. The worstcase running time of SIA is #### ### # ## for a #dimensional dataset of size n. SIATEC is an extension ..."
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Cited by 25 (11 self)
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We present a new algorithm, SIA, which discovers maximal repeated patterns in any set of points in Cartesian spaces of any dimensionality. The worstcase running time of SIA is #### ### # ## for a #dimensional dataset of size n. SIATEC is an extension
P.M.B.: A New Quartet Tree Heuristic for Hierarchical Clustering arXiv:cs/0606048
, 2006
"... We consider the problem of constructing an an optimalweight tree from the 3 () n weighted quartet 4 topologies on n objects, where optimality means that the summed weight of the embedded quartet topologies is optimal (so it can be the case that the optimal tree embeds all quartets as nonoptimal to ..."
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Cited by 13 (3 self)
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We consider the problem of constructing an an optimalweight tree from the 3 () n weighted quartet 4 topologies on n objects, where optimality means that the summed weight of the embedded quartet topologies is optimal (so it can be the case that the optimal tree embeds all quartets as nonoptimal topologies). We present a heuristic for reconstructing the optimalweight tree, and a canonical manner to derive the quartettopology weights from a given distance matrix. The method repeatedly transforms a bifurcating tree, with all objects involved as leaves, achieving a monotonic approximation to the exact single globally optimal tree. This contrasts to other heuristic search methods from biological phylogeny, like DNAML or quartet puzzling, which, repeatedly, incrementally construct a solution from a random order of objects, and subsequently add agreement values. We do not assume that there exists a true bifurcating supertree that embeds each quartet in the optimal topology, or represents the distance matrix faithfully—not even under the assumption that the weights or distances are corrupted by a measuring process. Our aim is to hierarchically cluster the input data as faithfully as possible, both phylogenetic data and data of completely different types. In our experiments with natural data, like genomic data, texts or music, the global optimum appears to be reached. Our method is capable of handling over 100 objects, possibly up to 1000 objects, while no existing quartet heuristic can computionally approximate the exact optimal solution of a quartet tree of more than about 20–30 objects without running for years. The method is implemented and available as public software. 1
Computing Pitch Names in Tonal Music: A Comparative Analysis of Pitch Spelling Algorithms
, 2006
"... A pitch spelling algorithm predicts the pitch names (e.g., C♯4, B♭5 etc.) of the notes in a passage of tonal music, when given the onsettime, MIDI note number and possibly the duration and voice of each note. A new algorithm, called ps13, was compared with the algorithms of LonguetHiggins, Cambour ..."
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Cited by 12 (7 self)
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A pitch spelling algorithm predicts the pitch names (e.g., C♯4, B♭5 etc.) of the notes in a passage of tonal music, when given the onsettime, MIDI note number and possibly the duration and voice of each note. A new algorithm, called ps13, was compared with the algorithms of LonguetHiggins, Cambouropoulos, Temperley and Chew and Chen by running various versions of these algorithms on a ‘clean’, scorederived test corpus, C, containing 195972 notes, equally divided between eight classical and baroque composers. The standard deviation of the accuracies achieved by each algorithm over the eight composers was used to measure style dependence (SD). The best versions of the algorithms were tested for robustness to temporal deviations by running them on a ‘noisy’ version of the test corpus, denoted by C ′. A version of ps13 called PS13s1 was the most accurate of the algorithms tested, achieving note accuracies of 99.44 % (SD = 0.45) on C and 99.41 % (SD = 0.50) on C ′. A realtime version of PS13s1 also outperformed the other realtime algorithms tested, achieving note accuracies of 99.19 % (SD = 0.51) on C and 99.16 % (SD = 0.53) on C ′. PS13s1 was also as fast and easy to implement as any of the other algorithms. New optimised versions
Results 1  10
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218